phd in artificial intelligence india

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Indian Institute of Technology Delhi

An institution of eminence, भारतीय प्रौद्योगिकी संस्थान दिल्ली, hauz khas, new delhi-110016, india, publish date: november 14, 2022, the school of artificial intelligence (scai).

The School of Artificial Intelligence (ScAI) set up in IIT Delhi has started broad based activities to bolster the AI related research in the country. Established in September last year, the School is aimed at meeting the strong global demand  for skilled AI manpower and spruce the AI ecosystem of the country.

Prof Mausam, Head School of Artificial Intelligence(ScAI) talks to Vanita Srivastava on the thrust areas, the future plans and more.

Edited Excerpts:

It has been just six months since the formal launch of the School. What have you able to attain so far? What have you planned for the future? We have made substantial progress in setting up the school. We have already launched the PhD programme in AI. We have submitted a proposal to the Board of Academic Programmes for starting an MTech programme in Machine Intelligence and Data Science. If this gets a nod, we can start it from July this year. Our advertisement for faculty recruiting is released, and applications have started coming in. We will initiate recruitment of core faculty soon. Around 15 faculty from several departments have already expressed their interest in becoming a joint faculty with the school, many more have joined us as associated faculty members. As part of the institution building process, I plan to start regular focused brainstorming sessions of all faculty members to develop research agendas in the various emerging themes and applications of AI.  Our website http://scai.iitd.ac.in  is also ready  where all the updates will be posted

What are the major thrust areas that you would be focussing on? On the basis of initial meetings of our current faculty members, five major applied research areas naturally emerged as our strength. These are: AI for health care, AI for Industry 4.0, Multilingual AI, Physically-grounded AI and AI for materials. The AI in health care group focuses on prediction of diseases from symptoms, automated radiology, personalized medicine and wearable robotics. Our research group in AI for materials targets the use of machine learning and natural language processing to predict the glass composition with a desired property. The traditional manufacturing processes are not always optimized; Industry 4.0 can help by detecting anomalies, and use optimization to increase efficiency in manufacturing processes. Multilingual AI area will help in translation of texts written in different languages, and will build multilingual dialogue systems and chatbots. Lastly, the physical AI group will develop methods to make robots more successful in their tasks, and also communicate effectively with humans. How do you plan to collaborate with the industry partners and spruce the funding? We are looking for funding at three different levels- government,  private donors and industry partners. A seed funding of 2 crore from one of our alumni, Mr Arun Duggal, got us started. We are aggressively connecting with more alumni and looking for a named sponsor to support the cause of developing AI at IIT Delhi. Donors can also join our league of founding donors -- they will be donors forever for the school. We have also started a preliminary round of talks with several industry partners. Our goal is to partner with companies who would be willing to have ties with us for atleast 4-5 years, possibly through their CSR funding.

Is it necessary to have a background in computer or electrical engineering for a PhD or MTech in AI? AI is emerging as a multidisciplinary field, with its roots in computer science, mathematics, cognitive science and electrical engineering, and its applications in almost every area. Thus, we invite PhD students from all backgrounds as long as they have knowledge of the fundamentals, irrespective of whether they studied it formally or learnt it themselves. In short, no -- a background in computer or electrical engineering is not a must for someone seeking an admission to Phd or M. Tech programme in AI. Building infrastructure would be a major challenge. How do you plan to address this? There are fundamentally three pillars in terms of infrastructural needs-data, algorithms and computational support. The first is taken care of by the domain experts, the second by core AI faculty and the last one we are gradually developing. Under this category, we recently submitted a proposal for building an AI supercomputer at IIT.

What were the major objectives for setting up the School of AI? AI technologies are driving global transformations and playing a pivotal role in social change. We fundamentally wanted to strengthen education and research in AI, Machine Learning and Data Science, and enable commercial and societal applications.  There is a lot of gap between demand and supply of AI professionals. There is therefore an urgent need for capacity building both for the industry and research. The School is essentially meant to provide single platform for students, faculty members, industry, non- profit organizations and policy makers, who share the common goal of making India an AI-powerhouse. What are the areas in IITD where AI is being used? There are more than 11 core researchers who have specialization in deep learning, reinforcement learning, adversarial networks, data mining, information retrieval, big data, probabilistic models, ethics of AI, logic based AI, and neuro symbolic AI. Besides there are more than 40 researchers engaged in health care, social media, computer vision, robotics, transportation, materials, languages, neuroscience, IoT and hardware. We also have strong partnerships with IBM Research on core AI algorithms and with AIIMS on healthcare applications. We regularly serve on governmental committees related to AI.

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Mehta Family

School of data science & artificial intelligence.

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INDIAN INSTITUTE OF TECHNOLOGY GUWAHATI

Mehta Family School of Data Science & Artificial Intelligence

Data Science and Artificial Intelligence @ IIT Guwahati

• Conducting research and development in cutting-edge areas in DS & AI
• Building and nurturing DS & AI talent to tackle challenging problems

Recent Notifications

Recent Seminars

Selected Publications

Recent Highlights

Algorithm-based prevention and reduction of cancer health disparity for data-disadvantaged population

The long-term cumulative data disadvantage of some groups is a critical barrier to developing racially unbiased machine learning models. To overcome this barrier, the performance of machine learning models can be improved using transfer learning for data-disadvantaged groups to develop racially unbiased models. With her expertise, Teena Sharma aims to make significant contributions to this field by answering some of the pressing questions. Know more here .

Marching ahead to create the 6G THz Testbed with Orbital Angular Momentum(OAM) & Multiplexing

Ratnajit Bhattacharjee's research in RF, facilitated by a consortium consisting of SAMEER, IIT Madras, IIT Guwahati, and IIT Patna, is driving India's efforts towards the development of 6G technology. The advancement of 6G is anticipated to enhance the progress of machine learning and artificial intelligence by enabling faster data transfer in IoT applications. Know more here .

Talk Series on Chat about Artificial Intelligence (CHAI)

CHAI revolves around engaging discussions about comprehending intelligence, both natural and artificial, and brainstorming its implications for applications in science and engineering. The members of the School come together whenever a speaker is arranged, creating an environment where we listen, exchange ideas, and (often) also enjoy a cup of chai together. Know more here .

Students making us proud

Our UG student members (2021-2025 Batch) - Aditya Gupta, Anant Kacholia, Aryan Lath, Devansh Bhardwaj, Nischay Nilabh, Subhash Patel, Varun Nagpal and Nityam Pareek represented IIT Guwahati in the Inter-IIT Technical Meet . The group, with their tenacity to think beyond the box about complex problem statements, won two gold medals and one bronze medal, making the institute proud. Besides this, Anant Kacholia with his two mates , also participated in Nobias Finance Investment Challenge 2023 and bagged the First prize of 5000 USD!

Listening to body sounds: Analyzing respiratory sound signals for design of AI-based disease screening methodologies

Thanks to improved non-invasive and easy capture of bodysounds using microphones and developments in data analysis techniques, acoustic epidemiology aided with artificial intelligence (AI) is gaining attention. In this project, Neeraj Sharma's group will focus on capture of lung sounds, and explore systematic analysis of these sound signals using approaches in signal processing and machine learning. The goal is to develop methods which allow detecting signatures in the sound signals which are associated with specific kinds of respiratory diseases. Know more about a related work on COVID-19 pursued by the group here

School of DS&AI Welcomes 2022 Batch of BTech Students, Expanding Capacity and Igniting a Quest for Impact

We are thrilled to extend a warm welcome to the incoming batch of BTech students for the year 2022 at the School of DS&AI. These students will join us as we collectively strive to explore deeper and create a positive impact on our world. The new students have come from various regions across India, having demonstrated their exceptional talents by excelling in the competitive IIT JEE (All India examination). To familiarize them with the School and its programs, an orientation meet was organized on 27th October 2022. It is worth mentioning that this year, the School has expanded its intake capacity from twenty students in 2021 to thirty students, enabling us to accommodate more aspiring individuals.

Reinforcement learning for mobile edge computing system

In an Internet of Things (IoT) based network, tasks arriving at individual nodes can be processed in-device or at a local Mobile Edge Computing (MEC) server. This project, led by Arghyadip Roy , focuses on the optimal resource allocation problem for tasks arriving in an MEC-based IoT network. To address the high complexities of achieving optimality, the aim is to develop low-complexity task scheduling schemes. Additionally, reinforcement learning (RL) based approaches will be developed that can learn the optimal policy by interacting with the environment. The performance of the RL-based schemes will be evaluated in system-level simulators. More details can be found in this paper on a related work of ours, and a presentation on the same is available here .

Analysis of facial tissue movements using AI

The eye and facial movements convey subtle information about the mental state (e.g., attention, intention, emotion) and physical state (e.g., age, health, fatigue) of a person. These movements, which generate facial expressions, are carefully scrutinized by humans in social settings. Debanga Raj Neog's lab is focussing on developing Artificial Intelligence (AI)-based systems for measuring, modeling, and animating eye gaze and facial tissue deformations for applications in healthcare and computer animation. The idea is to use high frame rate vision systems to capture human faces, and apply data-driven approaches to analyze and model facial expressions. In the healthcare sector, facial movement analysis can be used to develop tools for rapid assessments of mental health and to build patient-computer interaction systems. In computer graphics, it can help in creating real-time and hyper-realistic computer-generated animations of human eyes and faces in creating convincing and interactive animation characters. Know more here .

Modeling and prediction of nearly periodic phenomena

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We continue to design and offer new (advance) courses

We know teaching and learning feed each other. Our Faculty have designed specialized courses in DS&AI which they enjoy to teach, and also help student gain the depth and breadth in this exciting field. Know more here .

Campus gets another supercomputer

Named "Param Kamrup" , this is a 838 teraFLOPS super computer with 107 CPU nodes, 10 GPU nodes, 9 high memory nodes, 740 CPU cores, and several CUDA cores. Our data scientists are getting ready to crunch numbers with these machines!.

DS&AI at IIT Guwahati brings together faculty members specializing in diverse areas of Data Science and AI. We boast a highly skilled group of researchers who are dedicated to crafting innovative solutions for complex challenges encountered in India and worldwide.

Learn with Us

In the lively campus of IIT Guwahati, our students collaborate closely with faculty, engaging in the pursuit of knowledge and crafting solutions to unravel the "whys and why nots" of various challenges.

Partner with Us

Founded in 2021, we serve as the gateway to North-East India. We are open to collaboration with you as well. Our vision includes partnering with prominent names in AI research, such as technical companies, non-profits, and other universities, to achieve impactful outcomes together.

We're using DS&AI to solve challenging problems, but we can't do it without the best people and resources. Engage with us.

Prospective PhD Students

Are you considering pursuing a Ph.D. program in AI/ML? Yardi ScAI stands at the forefront of AI research, covering a wide range of areas such as machine learning, natural language processing, computer vision, robotics, Earth observation and more. Our faculty members are experts in their respective fields, leading cutting-edge research across various disciplines. Additionally, we offer generous grants to our Ph.D. scholars, on top of the standard stipend. An additional honorarium of 10,000 INR per month is provided to each student, contingent on their good performance in Ph.D. coursework and maintaining a CGPA of 8 or higher. Furthermore, we grant 2 lakhs INR for equipment to every Ph.D. student, and an additional 5 lakhs INR for travel grants to present papers in top conferences or publish journal articles as open access.

Admission Process

The admission process for PhD consist of three stages:

In the first stage, the candidates are short listed based on pre-approved shortlisting criteria set by the School. Note that shortlisting criteria of the school is more stringent than the minimum shortlisting criteria set by the institute. 

In the second stage, the shortlisted candidates are invited to appear for an in-person written test. The written test will be conducted at five locations in the country, namely (i) New Delhi, (ii) Mumbai, (iii) Kolkata, (iv) Hyderabad, and (v) Bengaluru, on 5th May 2024  (tentatively from 1 pm to 4 pm) . Shortlisted participants will be asked to give their preferences in one of these centres for giving their exam.  Though we will do our best to accommodate the candidate preferences, in case we run out of spots at a specific location, the candidate may be required to travel to Delhi to take the test.  During the exam, candidates must produce an original Government ID card such as AADHAAR, VOTERS ID, PAN CARD, DRIVING LICENCE, etc. for identification purposes. The written test has four sections: (a) General Aptitude, (b) Maths and Stats, (c) Data Structure and Algorithm and Programming, and (d) Machine Learning. Note that the total marks will be used for shortlisting for the next stage.  The syllabus and reading materials for the written exam can be found here . Some sample questions are also provided.

The candidates who qualify the second stage will be called for an interview (third stage). The final offers are made based on the performance in the interview only. 

The admission portal for PhD admission opens two times in a year (summer admission and winter admission). See admission link for further details.

Course Structure

Every PhD candidate at YARDI ScAI Has to complete minimum 9 credits of coursework while touching at least three buckets. Please check  course bucket  list for further details. Note that the bucket list gets updated periodically.

Admissions New Update

• Click here for the list of provisionally selected candidates to PhD/MSR/MTech (HVA) programs of School of AI, for the session strating Semester I, 2024-25. * NEW *
• Written Test for Shortlisted Candidates will be conducted on May 5, 2024 . Check out the Admission Process for more details
• Ph.D. Shortlisting Criteria:   click here   (Summer 2024-25) 
• If you want to view the information brochure, please  click here.
• Examination schedule, venue, and other details: here   
• Candidates who have qualified the written test have been sent an email regarding the details of the interview process. List of selected candidates is also available here . In case you have any concerns, feel free to contact the ScAI office. *NEW*
• If a student has any further queries, please write to office[AT]scai.iitd.ac.in for any clarification.

• Work with Us

Candidates who would like to apply for research programs in RBCDSAI should enroll for the PhD / MS program under Interdisciplinary Research Programme (IDRP) at IIT Madras. . The candidates must apply via the IIT Madras website, and choose the "Data Sciences & AI" stream for applying to RBCDSAI. Applicants must be fluent in at least one high-level programming language (C/C++/MATLAB/Python). A background in mathematics is highly preferred.

• Publications

The Department of Artificial Intelligence was previously established as the Centre of Excellence in Artificial Intelligence (CoEAI),  founded in 2018,  drives AI and ML innovation.  CoEAI aims to transform industries through groundbreaking research,  advanced education,  industry partnerships,  and entrepreneurship.  

Join us in building a future powered by AI.

Research Areas: Artificial Intelligence and Machine Learning, Complex and Social Networks, Data…

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Niloy Ganguly Professor Chairperson

Research Areas: Natural Language Pocessing, Artificial Intelligence, Digital Library, Machine Learning

[email protected]

Plaban Kumar Bhowmick Associate Professor Faculty

Research Areas: Natural Language ProcessingBig Data AnalyticsMachine LearningInformation Retrieval

[email protected]

Jiaul Hoque Paik Associate Professor Faculty

Research Areas: Machine Learning, Generative and graphical models, Climate Informatics and Climate…

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Adway Mitra Assistant Professor Faculty

Research Areas: Artificial Intelligence, Machine Learning

[email protected]

Koustav Rudra Assistant Professor Faculty

Research Areas: Deep Learning, Computer Vision, Computational Photography

[email protected]

Mahesh Mohan M. R. Assistant Professor Faculty

Research Areas: Learning based control for cyber physical and safety critical systems

[email protected]

Prabhat Kumar Mishra Assistant Professor Faculty

Research Areas: Image and Video Processing, Computer Vision, Machine Learning

[email protected]

Somdyuti Paul Assistant Professor Faculty

Dual Degree (M. Tech.) 

Micro-specialization

19 JUL 2024

Welcome session for M.Tech. and Ph.D. students: Details are communicated through email. Here we have…

19 JUN 2024

13 nov 2023, running projects.

100 Best universities for Artificial Intelligence (AI) in India

Updated: February 29, 2024

• Art & Design
• Computer Science
• Engineering
• Environmental Science
• Liberal Arts & Social Sciences
• Mathematics

Below is a list of best universities in India ranked based on their research performance in Artificial Intelligence (AI). A graph of 4.25M citations received by 475K academic papers made by 421 universities in India was used to calculate publications' ratings, which then were adjusted for release dates and added to final scores.

We don't distinguish between undergraduate and graduate programs nor do we adjust for current majors offered. You can find information about granted degrees on a university page but always double-check with the university website.

1. Indian Institute of Technology Delhi

For Artificial Intelligence (AI)

2. Indian Institute of Science

3. Indian Institute of Technology Kanpur

4. Indian Institute of Technology Kharagpur

5. Indian Institute of Technology Bombay

6. Indian Institute of Technology Madras

7. VIT University

8. Indian Statistical Institute

9. Jadavpur University

10. Indian Institute of Technology Roorkee

11. Anna University

12. Amrita University

13. National Institute of Technology, Rourkela

14. Thapar Institute of Engineering and Technology

15. Indian Institute of Technology Guwahati

16. Banaras Hindu University

17. Delhi Technological University

18. National Institute of Technology, Tiruchirappalli

19. Amity University

20. Manipal Academy of Higher Education

21. University of Delhi

22. Indian School of Mines

23. Birla Institute of Technology and Science

24. SRM Institute of Science and Technology

25. Savitribai Phule Pune University

26. National Institute of Technology, Kurukshetra

27. Indian Institute of Technology Hyderabad

28. Indian Institute of Engineering Science and Technology, Shibpur

29. National Institute of Technology, Silchar

30. Sardar Vallabhbhai National Institute of Technology, Surat

31. National Institute of Technology, Karnataka

32. Siksha O Anusandhan University

33. National Institute of Technology, Durgapur

34. Sathyabama Institute of Science and Technology

35. KIIT University

36. University of Calcutta

37. K L University

38. National Institute of Technology, Raipur

39. Motilal Nehru National Institute of Technology Allahabad

40. National Institute of Technology, Calicut

41. SASTRA University

42. Indian Institute of Technology Indore

43. Indian Institute of Information Technology Allahabad

44. Tata Institute of Fundamental Research

45. International Institute of Information Technology, Hyderabad

46. National Islamic University

47. Annamalai University

48. Panjab University

49. National Institute of Technology, Warangal

50. Malaviya National Institute of Technology, Jaipur

51. Aligarh Muslim University

52. Maulana Azad National Institute of Technology

53. Jawaharlal Nehru University

54. Pondicherry University

55. Birla Institute of Technology

56. University of Hyderabad

57. University of Kalyani

58. Guru Gobind Singh Indraprastha University

59. Indraprastha Institute of Information Technology

60. Visvesvaraya National Institute of Technology

61. Jaypee Institute of Information Technology

62. Veer Surendra Sai University of Technology

63. Indian Institute of Technology Patna

64. Karunya Institute of Technology and Sciences

65. National Institute of Technology, Hamirpur

66. Lovely Professional University

67. Bharathiar University

68. Indian Institute of Technology, BHU

69. Jawaharlal Nehru Technological University

70. Kalasalingam University

71. Graphic Era University

72. National Institute of Technology, Patna

73. Chitkara University - Punjab

74. Indian Institute of Information Technology and Management Gwalior

75. Saveetha University

76. Chandigarh University

77. PDPM Indian Institute of Information Technology, Design and Manufacturing

78. Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology

79. All India Institute of Medical Sciences Delhi

80. Indian Institute of Technology Bhubaneswar

81. Cochin University of Science and Technology

82. University of Mumbai

83. Vidyasagar University

84. Jawaharlal Nehru Technological University, Kakinada

85. Dr. B R Ambedkar National Institute of Technology Jalandhar

86. PES University

87. Punjabi University Patiala

88. Christ University

89. Andhra University

90. Symbiosis International University

91. Galgotias University

92. Nirma University

93. Tezpur University

94. Sri Venkateswara University

95. University of Kashmir

96. GLA University

97. Gandhigram Rural University

98. Jaypee University of Information Technology

99. Gandhi Institute of Technology and Management

100. Hindustan Institute of Technology and Science

The best cities to study Artificial Intelligence (AI) in India based on the number of universities and their ranks are Delhi , Bangalore , Kanpur , and Kharagpur .

Computer Science subfields in India

• Data Science

Top Indian Institutes for Ph.D. in Data Science

More and more organizations are now opening up to endless possibilities that data holds, necessitating the presence of people who are capable of unlocking meaningful and actionable insights from the vast amount of data. These people are called data scientists, and what they do—study data and extract insights, is called data science. Data science has become a prominent field over the last few years, and in India too. Consequently, many people are riding the wave and shifting to data-driven careers. A Ph.D. in data science is considered to be a prestigious qualification to advance in a data career. Here is a list of some top Indian institutes for Ph.D. in data science.

The initial thought that almost every person seeking a Ph.D in data science comes across is to explore the IITs. The Indian Institute(s) of Technology are one of the country’s most prestigious centers of (engineering) excellence. 

Some Ph.D. in Data Science Programs at IITs

We have covered a few IITs offering comprehensive science and data science doctorates. Have a look.

The Indian Institute of Technology Madras (IITM) is one of the oldest institutes catering to higher education in engineering. It was established in 1959 by Prof. Humayun Kabir, Union Minister of Scientific Research and Cultural Affairs, after the first Indo-German agreement in Bonn. With over 16 academic departments and some research centers, IITM ranks among the top engineering institutes for postgraduate and doctorate students.

IIT Madras offers research programs in several areas like biotechnology, ocean engineering, structural analysis, element modeling, data sciences, and many more. The institute also offers joint Ph.D. programs with universities like the University of Singapore, the University of Bordeaux, Michigan State University, and a few others. Refer to the research programs’ page for more details.

• IIT Hyderabad

The Indian Institute of Technology Hyderabad (IITH) , a relatively newer IIT institution branch, was founded in 2008. As one of the nation’s most sought-after institutions for science and technology, IITH has continuously been listed among the top 10 engineering and Ph.D. institutes in India. The institute offers a number of undergraduate, postgraduate, and doctoral programs in all classical engineering disciplines and interdisciplinary areas like artificial intelligence.

IITH offers regular Ph.D. programs in the following departments: biomedical engineering, artificial intelligence, chemical engineering, climate change, physics, engineering science, civil engineering, mechanical & aerospace engineering, and many other domains. Specifically for a Ph.D. in artificial intelligence or a Ph.D. in data science, in India, IITH is an excellent place to enroll. To know more about the courses and admission requirements, refer here .

Indian Institute of Technology Delhi (IITD) is one of the 23 Centers of Excellence for engineering, research, and development in science and technology. It was established in 1961 as College of Engineering and was later renamed as IIT-Delhi in 1963. The institute is an excellent place for students to wish to study engineering, sciences, and even business administration.

The Yardi School of Artificial Intelligence (ScAI) at IIT Delhi offers comprehensive Ph.D. programs in both core and advanced artificial intelligence and data science. The data science Ph.D. course will also include machine learning techniques, mathematical foundations, and applications of artificial intelligence in the field. For more information on Ph.D. programs offered by the Yardi School of Artificial Intelligence, refer to the website .

• IIT Jodhpur

IITJ, the Indian Institute of Technology Jodhpur , was established to promote technology-based education and research in India in 2008. The Institute is committed to a multidisciplinary approach to developing new technologies and furthering them as educational courses via its cutting-edge laboratories, academic degree-related activities, and coordinated research efforts. 

IITJ offers M.Tech, data science Ph.D. courses, and an integrated data science Ph.D. The doctoral program focuses on inculcating deep knowledge and computational thinking skills among students. Students who enroll in Ph.D. in data science will also develop a strong understanding of machine learning, data mining, modeling & simulation, numerical analysis, and other data-related technologies. For details, check out the main website . 

Read More: Made In Bengaluru: A Kannada Film To Be Released In The Metaverse

Some Other Data Science Ph.D. Courses in India

Have a look at some more data science Ph.D. courses and institutes offering them.

• BITS Pilani

Birla Institute of Technology & Science, BITS Pilani , is the epitome of higher education. The Institute was established in the early 1900s as a small school to train youth. Over the years, it expanded into a set of colleges for higher education that later formed the university. BITS is known to provide top-of-the-line technical education to students all over the world who are admitted on a merit basis. 

Ph.D. in Data Science at BITS PILANI

BITS Pilani offers several areas of doctoral education in the data science domain. These areas include:

• Artificial intelligence, Machine Learning, and Data Mining
• Computer Architecture, Embedded Systems & Robotics
• Data Warehousing, Databases, and Advanced Databases
• High-Performance Computing and Distributed Systems
• Image Processing & Multimedia
• Networking and Mobile Computing
• Algorithms & Theoretical Computer Science 

The institute primarily offers full-time doctoral courses. Other details, including the fee structure and shortlisting criteria, can be found on the website .

• Ph.D. in Data Science: Christ (deemed to be) University

The CHRIST University was founded by St. Kuriakose Elias Chavara, a social reformer, and educationist. It was established as a college with an aim to bring breakthroughs in the Indian higher education landscape using modern curricula and holistic education. After several years of operating as a college, the UGC (University Grants Commission) accredited it with the autonomy of being identified as an institution in 2006. Since then, the (deemed to be) university has focused on Bachelor’s, Master, and Doctoral degrees in social sciences, engineering, architecture, sciences, commerce, and law.

CHRIST’s doctorate of data science is a unique amalgamation of computer science, mathematics, and statistics. The Ph.D. program also covers the underlying computational models and mathematical research to give students a dynamic learning experience in the data domain. For details about the course and course fee, check the course page .

• Indian Statistical Institute

If you are wondering which university is best for data science Ph.D. in India, then the Indian Statistical Institute (ISI) is your answer. Mahalanobis established the prestigious institute in 1931 as a small statistics laboratory in the Presidency College. Soon enough, many people began taking an interest in statistical research, and the wave took over the institute. ISI offers several prestigious postgraduate and doctoral programs across multiple fields, like humanities, commerce, IT, engineering & architecture, management, and sciences. 

For a Ph.D. in data science domain, ISI offers research fellowships in Statistics, Quantitative Economics, Computer Sciences, Mathematics, and Reliability & Operations Research. Specifically, ISI is an excellent option if you are looking for a Ph.D. in statistics in India. To know more about the program details, refer to the website . 

• Ph.D. in Data Science at IISc Bangalore

The Indian Institute of Science (IISc) Bangalore is a reputed research university for higher education in the fields of engineering, management, design, and science. The Department of Computational and Data Sciences (CDS), a division of IISc that specializes in data sciences and computations, grants research-based doctoral degrees. 

CDS offers two research-based routes for students seeking admission to a Ph.D. in data science: Computational Science (CP) and Computer & Data Systems (CS). CDS-CP includes computational methods in areas like bio-molecular computation, structural biology, medical imaging, and other related fields. CDS-CS designs, implements, and evaluates computer hardware and software systems. For more information, refer to the website .

• Woxsen University 

Looking for an integrated data science Ph.D. in India, Woxsen University is a top university in India for data science Ph.D. and is one of the most reliable, privately-held universities in the southern part of the country. Founded in 2014, the university ranks well amongst emerging engineering and business colleges. The university aims at bringing new-age programs in multiple domains like management, architecture, design, liberal arts & sciences, and a few others. 

In doctoral programs, Woxsen offers both full-time, and executive Ph.D. focused on research and interdisciplinary subjects. It also offers a comprehensive, fully residential Ph.D. in data science. For more information, refer to the website .

• Ph.D. in Data Science at IIT Guwahati

Indian Institute of Technology (IIT) Guwahati is a prestigious higher education institution established in 1994. Being the only institute that comes in the top 100 world universities under 50 years of age, it offers comprehensive graduate, postgraduate and doctoral programs. The Mehta Family School of Data Science and Artificial Intelligence (MFSDS&AI) offers several Ph.D. courses at IIT Guwahati:

• Ph.D. in AI 
• Ph.D. in Machine Learning, Deep Learning, or Reinforcement Learning
• Ph.D. In Computer Vision, Natural Language Processing, and High-Performance Computing.

For more information about the courses and admission requirements, refer to the website .

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BE/ B.Tech degree in the relevant discipline OR Master’s degree in Science / Economics, Geography, Psychology, Management, Commerce, Operations Research, Computer Science OR Master’s degree in Engineering / Technology / Architecture/ Agriculture / Pharmacy / Veterinary Sciences.

A valid score in GATE/ NET/ JRF/ GPAT followed by a written test (for some departments) and interview round.

Course Details

Along with B.Sc (Research) and PG courses, the institute also offers Integrated PhD program in selected disciplines. Candidates with a Bachelor’s degree in Biology/Biotechnology/ Chemistry/ Physics/ Mathematics/ Pharmacy/ Veterinary Sciences/ Agriculture with a valid JAM score are eligible to apply to this program. Those in the final year of their qualifying examination and awaiting results are also eligible to apply.

• BE / B.Tech degree holders who qualify Mathematics/Mathematical Statistics paper in JAM can apply for Mathematical Sciences 
• Those who appear in Biotechnology paper in JAM can apply for Biological Sciences discipline
• Candidates will be shortlisted on the basis of JAM score for all the four disciplines.
• In case of Physical Sciences discipline, JEST will also be considered for shortlisting.

How to Apply for M.Tech, M.Des, M.Mgt & Ph.D. at IISc Bangalore?

The application form can be filled by following the below-listed steps:

• Candidates seeking admission can submit the application forms through online mode from the official website.
• The application fee is  INR 800  for GN/OBC/KM candidates and  INR 400  for SC/ST/PWD categories.
• Application fee can be submitted online through any of the following online payment modes viz. Net-banking, Visa Card/ Master Card, Debit/Credit Cards.
• Candidates intimated for the aptitude test/group discussion and interview should bring the attested copies of all their transcripts (marks cards from SSLC or its equivalent onwards, degree certificates of the qualifying examinations, etc.).

Candidates seeking admission to the Integrated PhD programs should qualify in JAM and must update the corresponding scores immediately upon the declaration of JAM results. Candidates who have appeared in the following papers in JAM are eligible to apply for respective disciplines which are as follows:

• Physical Sciences – Physics (PH) (also those who clear JEST)
• Chemical Sciences – Chemistry (CY) or Biological Sciences (BL) or Physics (PH)
• Biological Sciences – Biological Sciences (BL) or Biotechnology (BT) or Chemistry (CY) or Mathematics (MA) or Physics (PH)
• Mathematical Sciences – Mathematics (MA), Mathematical Statistics (MS)

Ph.D (Artificial Intelligence) Comparison

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Indian Institute of Science, Bangalore

• Ph.D. in Artificial Intelligence
• About Course

Ph.D. in Artificial Intelligence - Indian Institute of Science, Bangalore

An  Artificial Intelligence ( AI) Ph.D. focuses on the development of advanced computer systems that can mimic human decision-making processes. It is a rapidly growing field and researchers in this area are highly sought after. The program requires candidates to have previous work experience in a related field or be an expert in a specific programming language. Students are also required to meet the minimum English language requirements set by the university. Usually, they must complete the TOEFL or IELTS exam to qualify for the degree.

A Ph.D. in AI is an excellent choice for individuals who want to develop the next generation of AI. The program is designed to foster creative thinking by exposing students to deep problems and working with talented and technically creative people. A career in  artificial intelligence  is rewarding because of its broad scope and potential to help the world. However, it is also not for everyone. Graduates will often spend a considerable amount of time at the university and do not receive a salary after graduation.

Graduate work in AI requires advanced mathematics and algorithms . It also requires solid programming languages. It takes a long time to complete a Ph.D., which is a common problem for graduate students. Nevertheless, the research will have a significant impact on society. It is a great option for those looking to become AI experts. The tuition fee for a Ph.D. in AI is around fifty thousand to five lakh INR Rupees students. The cost for international students is around PS25,000 per academic year.

Ph.D. in  Artificial Intelligence  Eligibility

Candidates who want to take admission in Ph.D. must have a post-graduate degree in Artificial Intelligence and its relevant discipline with at least 55% marks from a recognized university and must have passed the national level entrance examination or university level entrance examination. National level entrance exams like UGC NET / UGC CSIR NET / GATE / SLET or University entrance exam consisting of written tests and personal interviews.

The Benefits of a Ph.D. in Artificial Intelligence

The advantages of a Ph.D. in AI go beyond the benefits of a high-paying position. It can also open the door to a career in academia, where you can propose and oversee your own research projects. In addition, you can become a professor and influence the next generation of AI experts. You can make use of university resources, facilities, and industrial ties in your research.

The research opportunities in artificial intelligence are numerous. You can pursue a career in AI research in one of its many fields, from computer science to entrepreneurship . The demand for qualified AI specialists is increasing every year, which means you'll be able to earn a high salary. You can also pursue a Ph.D. in AI to advance your career in the field. You'll have the opportunity to use AI in many different fields, including human-computer interaction, robotics, and machine learning.

The field of artificial intelligence is highly diverse, and there are many career options available. As computer systems have become more integrated into our lives, the need for experts has soared. The demand for AI professionals has grown rapidly, leading to a lucrative salary and high job security. Whether you choose to work as an AI researcher, a data scientist, a robotics engineer, or a programmer, your future is bright with the benefits of a Ph.D. in AI .

Career and Job Opportunities of Ph.D. in Artificial Intelligence

After graduating with your Ph.D. in  artificial intelligence , you can pursue a variety of careers. One of the most sought-after areas of work in academia. You can propose your own research project and supervise students. As an AI professor, you can shape the next generation of experts in AI. You can also take advantage of the university's facilities and industrial ties.

The artificial intelligence field is rapidly advancing, making it a hot field. Although it might sound easy, getting into this field requires guts and know-how. More than half of senior AI professionals report a skills gap in the recruitment of new scientists. A recent study by Ernst & Young shows that the market for AI specialists will increase by 15% over the next ten years.

Many job openings in  artificial intelligence  require a Ph.D. degree, but there are also positions available online for those who have an undergraduate degree in the area. Those with a bachelor's degree in computer science are the best candidates for this type of job. The field is highly competitive, and those with a master's degree are the most likely to find success in it.

The Future Scope of a Ph.D. in Artificial Intelligence

The Ph.D. program in  artificial intelligence  offers students the chance to pursue research in an area that interests them. After completing the coursework, they will be able to propose their own research projects and supervise graduate students. The doctoral program requires four to five years of study and can help you to gain experience in the computer science field and the field of smart machines. In addition, the doctoral program prepares you to work in a research lab or for an industry partner.

A Ph.D. in Artificial Intelligence prepares graduates for a variety of careers in the field. They can become Business Intelligence Developers or Business Intelligence Researchers. In the public and private sectors, AI experts are needed for a variety of jobs, from determining market trends to designing games. They may even be involved in developing expert systems and robotics.

The future scope of a Ph.D. in Artificial Intelligence will require a strong background in artificial intelligence and machine learning. Students will be able to contribute to this emerging technology and apply their expertise to a variety of fields. The applications of AI include engineering applications, including automated tasks and parametric modeling. AI researchers may also find useful work in medical applications, including data-science approaches to identify patterns in human illness. Financial applications include machine learning platforms, which are able to process enormous amounts of data.

Ph.D. Research Programme duration

The Ph.D. in Artificial Intelligence course is a minimum of 3 years and a maximum of 5 duration. This depends on the university offering the course.

Fees for research program for Virology

The average fee for Ph.D. in Artificial Intelligence degree is between INR 50000 and INR 500000.

Bangalore Urban

Delivery Mode

Eligibility

Masters degree in Artificial Intelligence or relevant subjects + the candidates should have cleared the Entrance test conducted by the respective university.

Type of Course

Indian institute of science, bangalore highlights.

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Artificial Intelligence

Government of India has taken several steps to promote upskilling or reskilling in the field of Artificial Intelligence which include the following: -

• Ministry of Electronics and IT (MeitY) has initiated a programme titled FutureSkills PRIME ( www.futureskillsprime.in ) in collaboration with NASSCOM, a B2C framework for re-skilling/ up-skilling of IT professionals in 10 Emerging are as including Artificial Intelligence. So far, 7 Lakh candidates have signed-up on the FutureSkills PRIME Portal, out of which, 1.2 lakh candidates have completed their courses. In addition, 524 Trainers and 4292 Government Officials have been trained on these technologies by NIELIT/C-DAC Resource Centres, and around 1.3 lakh unique learners have collectively earned 8.9 lakh ‘badges’ in recognition of having completed bite- sized digital fluency content.Under Artificial Intelligence, 36,528 candidates are enrolled in deep– skilling courses and 47,744 candidates are enrolled in Foundation courses.
• Government has published the National Strategy for Artificial Intelligence in June 2018 and proposes to develop an ecosystem for the research and adoption of Artificial Intelligence i.e. #AIFOR ALL.
• Government has launched ‘National AI Portal’ ( https://indiaai.gov.in/ ) which is a repository of Artificial Intelligence (AI) based initiatives in the country at a single place. As on date, there are 1024 national and international articles, 655 news, 200 videos, 90 research reports, 279 Startups, 120 Government initiatives listed at National AI Portal.

In addition, various steps have been taken to promote capacity building in Artificial Intelligence which include the following:

• Government has initiated ‘Visvesvaraya PhD Scheme’ with an objective to enhance the number of PhDs in Electronics System Design & Manufacturing (ESDM) and IT/IT Enabled Services (IT/ITES) sectors in the country. The research areas under the scheme include Artificial Intelligence (covering 82 PhD fellows) and Machine Learning (covering 59 PhD fellows).
• National Programme on Responsible Use of AI for Youth: With the objective to empower the youth to become AI ready and help reduce the skill gap, government along with Industry partner has started this initiative to promote AI awareness among Government school going children. In Phase I, 50,666 students and 2536 teachers from 2252 schools from 35 States and UTs attended orientation sessions on AI. In Phase II, 100 teams have been short listed and have undergone extensive mentoring by AI experts. In Phase-III, Top 20 students have demonstrated their solutions in the national conference.
• To foster innovation through research, government has created several ‘Centres of Excellence’ on various Emerging Technologies including Artificial Intelligence. These centres connect various entities such as startups, enterprises, venture capitalists, government and academia to look into problem statements and develop innovative solutions.
• Department of Science & Technology is implementing the National Mission on Interdisciplinary Cyber-Physical Systems (NM-ICPS) to promote R&D, Human Resource Development (HRD), Technology Development, Entrepreneurship Development, International Collaboration etc. As part of the Mission implementation, 25 Technology Innovation Hubs (this) have been established in reputed institutes across the country in advanced technologies including Machine Learning and Artificial Intelligence.
• Government of India has also joined the league of leading economies including USA, UK, EU, Australia, Canada, France, Germany, Italy, Japan, Mexico, New Zealand, Republic of Korea, Singapore as a founding member of the Global Partnership on Artificial Intelligence (GPAI), which is an international and multi-stakeholder initiative to guide the responsible development and use of AI, grounded in human rights, inclusion, diversity, innovation, and economic growth.
• Government of India organized Responsible AI for Social Empowerment (RAISE) in 2020, a first-of-its-kind global meeting of minds on Artificial Intelligence to drive India’s vision and roadmap for social transformation, inclusion and empowerment through responsible AI. It was attended by 79,000+ stakeholders from academia, research, industry and government representatives from 147 participating countries.320 distinguished speakers from 21 countries participated in the event.

The initiatives mentioned above are focusing on digital enablement of citizensin the field of Artificial Intelligence including those belonging to the Tier 2 & Tier 3 cities. Further, the FutureSkills PRIME programmefollows an ‘aggregator of aggregators’ approach for digital skills training on a national scale and is hosted as an online B2Ce-commerce platform, thereby also enabling citizens in Tier 2 & Tier 3 cities to participate in the programme. To further strengthen the physical and digital connectivity, 40 C-DAC/NIELIT Centres spread across the country are also institutionalizing blended-learning programmes, in a hub and spoke mode, as Lead & Co-Lead Resource Centres.

Further, the FutureSkills PRIME programme targets to re-skill/ up-skill aspirants in emerging technologies so that they stay relevant in their present job with improved prospects, besides finding new avenues in future job-roles.The programme also targets those whose may have lost their existing jobs due to disruptive and emerging technologies. Towards this, the programme takes into account employment linkages, such as a ‘Career Prime’ web-page on the platform and an integrated ‘Career Portal’,which provides information on IT-ITeS jobs, internships, apprenticeships, hackathons etc.

Under FutureSkills PRIME, incentives are available to the trainees, including those from economically weaker backgrounds, after the learner is successfully assessed and certified. The incentive mechanism is aimed at motivating the learner to successfully complete the online up- skilling/re-skilling programs.

This information was given by the Minister of State for Electronics & Information Technology, Shri Rajeev Chandrasekhar in a written reply to a question in Lok Sabha today.

Machine Learning - CMU

Phd program in machine learning.

Carnegie Mellon University's doctoral program in Machine Learning is designed to train students to become tomorrow's leaders through a combination of interdisciplinary coursework, hands-on applications, and cutting-edge research. Graduates of the Ph.D. program in Machine Learning will be uniquely positioned to pioneer new developments in the field, and to be leaders in both industry and academia.

Understanding the most effective ways of using the vast amounts of data that are now being stored is a significant challenge to society, and therefore to science and technology, as it seeks to obtain a return on the huge investment that is being made in computerization and data collection. Advances in the development of automated techniques for data analysis and decision making requires interdisciplinary work in areas such as machine learning algorithms and foundations, statistics, complexity theory, optimization, data mining, etc.

The Ph.D. Program in Machine Learning is for students who are interested in research in Machine Learning.  For questions and concerns, please   contact us .

The PhD program is a full-time in-person committment and is not offered on-line or part-time.

PhD Requirements

Requirements for the phd in machine learning.

• Completion of required courses , (6 Core Courses + 1 Elective)
• Mastery of proficiencies in Teaching and Presentation skills.
• Successful defense of a Ph.D. thesis.

Teaching Ph.D. students are required to serve as Teaching Assistants for two semesters in Machine Learning courses (10-xxx), beginning in their second year. This fulfills their Teaching Skills requirement.

Conference Presentation Skills During their second or third year, Ph.D. students must give a talk at least 30 minutes long, and invite members of the Speaking Skills committee to attend and evaluate it.

Research It is expected that all Ph.D. students engage in active research from their first semester. Moreover, advisor selection occurs in the first month of entering the Ph.D. program, with the option to change at a later time. Roughly half of a student's time should be allocated to research and lab work, and half to courses until these are completed.

Master of Science in Machine Learning Research - along the way to your PhD Degree.

Other Requirements In addition, students must follow all university policies and procedures .

Rules for the MLD PhD Thesis Committee (applicable to all ML PhDs): The committee should be assembled by the student and their advisor, and approved by the PhD Program Director(s).  It must include:

• At least one MLD Core Faculty member
• At least one additional MLD Core or Affiliated Faculty member
• At least one External Member, usually meaning external to CMU
• A total of at least four members, including the advisor who is the committee chair

Financial Support

Application Information

For applicants applying in Fall 2024 for a start date of August 2025 in the Machine Learning PhD program, GRE Scores are OPTIONAL. The committee uses GRE scores to gauge quantitative skills, and to a lesser extent, also verbal skills.

Proof of English Language Proficiency If you will be studying on an F-1 or J-1 visa, and English is not a native language for you (native language…meaning spoken at home and from birth), we are required to formally evaluate your English proficiency. We require applicants who will be studying on an F-1 or J-1 visa, and for whom English is not a native language, to demonstrate English proficiency via one of these standardized tests: TOEFL (preferred), IELTS, or Duolingo.  We discourage the use of the "TOEFL ITP Plus for China," since speaking is not scored. We do not issue waivers for non-native speakers of English.   In particular, we do not issue waivers based on previous study at a U.S. high school, college, or university.  We also do not issue waivers based on previous study at an English-language high school, college, or university outside of the United States.  No amount of educational experience in English, regardless of which country it occurred in, will result in a test waiver.

Submit valid, recent scores:   If as described above you are required to submit proof of English proficiency, your TOEFL, IELTS or Duolingo test scores will be considered valid as follows: If you have not received a bachelor’s degree in the U.S., you will need to submit an English proficiency score no older than two years. (scores from exams taken before Sept. 1, 2023, will not be accepted.) If you are currently working on or have received a bachelor's and/or a master's degree in the U.S., you may submit an expired test score up to five years old. (scores from exams taken before Sept. 1, 2019, will not be accepted.)

Graduate Online Application

• Admissions application opens September 4, 2024
• Early Application Deadline – November 20, 2024 (3:00 p.m. EST)
• Final Application Deadline - December 11, 2024 (3:00 p.m. EST)

• Doing a PhD in Artificial Intelligence

Artificial intelligence and intelligent systems are thought to be the key to the next ‘industrial revolution’. In a data-rich world, developing an artificial intelligence which can learn from its experience and call on human behaviour to make decisions could change the way we live and offer endless economic, social and scientific applications. Nationwide, there is an increasing demand for AI workers, as the world is becoming more reliant on developing technology and automated systems. Consequently, more and more people are pursuing postgraduate research in AI.

What Does a PhD in Artificial Intelligence Focus On?

A PhD in artificial intelligence will give you a deep understanding of AI, allow you to contribute to the development of emerging technology, and equip you with highly applicable technical skills. For example, engineering applications of artificial intelligence include automation of tasks and parametric modelling. Medical applications include using data-science approaches to identify patterns of illness in clinical data. Financial applications include using machine learning platforms to crunch huge amounts of data and help credit lenders in analysing risk and assess potential borrowers.

Artificial Intelligence PhD programme can focus on:

• Machine learning
• Deep learning
• Natural language processing
• Deep neural network architecture
• Human-machine interaction
• Augmented reality
• And countless other areas

Browse PhDs in Artificial Intelligence

Application of artificial intelligence to multiphysics problems in materials design, from text to tech: shaping the future of physics-based simulations with ai-driven generative models, study of the human-vehicle interactions by a high-end dynamic driving simulator, coventry university postgraduate research studentships, discovery of solid state electrolytes using deep learning, entry requirements for a phd in artificial intelligence.

The entry requirements for a PhD in AI are typically an upper second-class honours degree (or international equivalent) in a relevant subject from an accredited university. Subjects considered relevant to artificial intelligence include computer science, engineering, mathematics, statistics, electronics/electrical engineering or science.

Some research courses also require applicants to possess experience in programming, the desired programming language will be specific to the research project. Academic or work experience in machine learning or data science are typically favourable for applications.

International students will also need to meet several minimum English language requirements set by the university, usually as part of a TOEFL or IELTS exam.

Duration and Programme Types

Like most PhDs, a doctoral programme in Artificial Intelligence typically takes 3-4 years full-time, or 6 years part-time .

Aside from the traditional PhD, there is also the CDT PhD. Many Universities have Centres for Doctoral Training (CDTs) which are often funded by the UKRI centre . These CDTs can offer the CDT PhD which is a specialised PhD programme in artificial intelligence. The main difference between a standard PhD in artificial intelligence and a CDT PhD in artificial intelligence is that the latter includes additional modules which give candidates training in neuroscience, entrepreneurship, high performance computing, AI ethics and science communication.

Due to the different research areas you can pursue within the artificial intelligence field, the nature of programmes can vary. Some PhD research programmes are computational based and heavily reliant on coding, mathematics and lab work. Other research programmes can be people facing, involving questionnaires, for example to determine public perception on proposed legislation.

Costs and Funding

Annual tuition fees for PhDs in Artificial Intelligence are typically around £4,000 to £5,000 for UK/EU students. Tuition fees for international students are usually much higher, typically around £25,000 per academic year.

A variety of scholarships and funding support options are available for postgraduate study. For Artificial Intelligence in particular, the UKRI and ESPRC offer a number of studentships and CDT opportunities across varies universities. Many universities have research centres which are partnered with UK research councils and offer fully funded programmes. Funding is generally available for UK/EU students. International students are also eligible for some funding opportunities, but these tend to be less widely available.

Available Career Paths in AI

One of the key advantages of Artificial Intelligence is that it has a wide range of applications, and hence there are many career paths available. As computer systems and data have become more integrated in everyday life, the demand for experts in AI has grown rapidly. This high demand has resulted in many high job security and lucrative salaries.

Examples destinations for an AI PhD student include:

Data Analyst – If you are very analytical research student, you may use your artificial intelligence PhD to pursue a career in data science or analysis. Data analysts can be found in engineering, finance, healthcare, and everywhere in between. They are responsible for data crunching and using their skills to present complex information in a clear manner – visually and orally. Typical duties include record management, maintaining automated processes, monitoring analytics and KPIs, improving algorithms, and creating dashboards for clients. The average salary for data analysts in the UK is around £30,000 – £45,000, though this number can increase drastically depending on the sector.

Cyber Security – As cyber-attacks are becoming more commonplace, industries are looking to develop their cyber security, and salaries are seeing a sharp increase accordingly. AI doctorates are well placed for a career in cyber security, and typical career destinations include security analysts, penetration testers, systems engineers, web developers and cybersecurity consultants. In these roles, you will be responsible for protecting IT infrastructure and help develop security systems.

Machine learning – Often those with a PhD in AI become machine learning engineers, responsible for the development of intelligent systems. Machine learning is a subset of AI which focuses on the idea that machines can be programmed to learn from data and experience to improve decision making without human input. Machine learning is perhaps at the forefront of AI research, and there are numerous programmes look to improve its capabilities. This is well suited for those who enjoy the mathematical and programming side of computer science. Typical duties include managing data pipelines, developing algorithms, liaising with stakeholders, analysing datasets, and leading software design. Entry level salaries are around £35,000 and can exceed £150,000 with experience. Deep learning is similar to machine learning, the main difference is that deep learning aims to create artificial ‘neural networks’.

Postgraduate research often leads to an academic career. As an academic you can propose your own research projects based on your interest and supervise students. As a professor you can shape the next generation of AI experts and as a researcher you can make use of a university’s department resources, facilities and industrial ties to work with cutting edge technology and push the boundaries of our knowledge.

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MastersInAI.org

PhD in Artificial Intelligence Programs

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Universities offer a variety of Doctor of Philosophy (Ph.D.) programs related to Artificial Intelligence (AI.) Some of these are titled as Ph.D.s in AI, whereas most are Ph.D.s in Computer Science or related engineering disciplines with a specialization or focus in AI. Admissions requirements usually include a related bachelor’s degree and, sometimes, a master’s degree. Moreover, most Ph.D. programs expect academic excellence and strong recommendations. The AI Ph.D. programs take three to five or more years, depending on if you have a master’s and the complexity of your dissertation. People with Ph.D.s in AI usually go on to tenure track professorships, postdoctoral research positions, or high-level software engineering positions.

What Are Artificial Intelligence Ph.D. Programs?

Ph.D. programs in AI focus on mastering advanced theoretical subjects, such as decision theory, algorithms, optimization, and stochastic processes. Artificial intelligence covers anything where a computer behaves, rationalizes, or learns like a human. Ph.D.s are usually the endpoint to a long educational career. By the time scholars earn Ph.D.s, they have probably been in school for well over 20 years.

People with an AI Ph.D. degree are capable of formulating and executing novel research into the subtopics of AI. Some of the subtopics include:

• Environment adaptation in self-driving vehicles
• Natural language processing in robotics
• Cheating detection in higher education
• Diagnosing and treating diseased in healthcare

AI Ph.D. programs require candidates to focus most of their coursework and research on AI topics. Most culminate in a dissertation of published research. Many AI Ph.D. recipients’ dissertations are published in peer-reviewed journals or presented at industry-leading conferences. They go on to lead careers as experts in AI technology.

Types of Artificial Intelligence Ph.D. Programs

Most AI Ph.D. programs are a Ph.D. in Computer Science with a concentration in AI. These degrees involve general, advanced level computer science courses for the first year or two and then specialize in AI courses and research for the remainder of the curriculum.

AI Ph.D.s offered in other colleges like Computer Engineering, Systems Engineering, Mechanical Engineering, or Electrical Engineering are similar to Ph.D.s in Computer Science. They often involve similar coursework and research. For instance, colleges like Indiana University Bloomington’s Computing and Engineering have departments specializing in AI or Intelligent Engineering. Some colleges, however, may focus more on a specific discipline. For example, a Ph.D. in Mechanical Engineering with an AI focus is more likely to involve electric vehicles than targeted online advertising.

Some AI programs fall under a Computational Linguistics specialization, like CUNY . These programs emphasize the natural language processing aspect of AI. Computational Linguistics programs still involve significant computer science and engineering but also require advanced knowledge in language and speech.

Other unique programs offer a joint Ph.D. with non-engineering disciplines, such as Carnegie Mellon’s Joint Ph.D. in Machine Learning and Public Policy, Statistics, or Neural Computation .

How Ph.D. in Artificial Intelligence Programs Work

Ph.D. programs usually take three to six years to complete. For example, Harvard lays out a three+ year track where the last year(s) is spent completing your research and defending your dissertation. Many Ph.D. programs have a residency requirement where you must take classes on-campus for one to three years. Moreover, most universities, such as Brandeis , require Ph.D. students to grade and/or teach for one to four semesters. Despite these requirements, several Ph.D. programs allow for part-time or full-time students, like Drexel .

Admissions Requirements

Ph.D. programs in AI admit the strongest students. Most applications require a resume, transcripts, letters of recommendation, and a statement of interest. Many programs require a minimum undergraduate GPA of 3.0 or higher, although some allow for statements of explanation if you have a lower GPA due to illness or other excusable causes for a low GPA.

Many universities, like Cornell , recently made the GRE either optional or not required because the GRE provides little prediction into the success of research and represents a COVID-19 risk. These programs may require the GRE again in the future. However, many schools still require the IELTS/TOEFL for international applicants.

Curriculum and Coursework

The curriculum for AI Ph.D.s varies based on the applicants’ prior education for many universities. Some programs allow applicants to receive credit for relevant master’s programs completed prior to admission. The programs require about 30 hours of advanced research and classes. Other programs do not give credit for master’s programs completed elsewhere. These require over 60 hours of electives, in addition to the 30-hours of fundamental and core classes in addition to the advanced courses.

For programs with more specific specialties, the courses are usually narrowly focused. For example, Duke’s Dynamics, Robotics, and Controls track requires ten classes, at least three of which are focused on AI as it relates to robotics. Others allow for non-AI-specific courses such as computer networks.

Many Ph.D. programs have strict GPA requirements to remain in the program. For example, Northeastern requires PhD candidates to maintain at least a 3.5 GPA. Other programs automatically dismiss students with too many Cs in courses.

Common specializations include:

• Computational Linguistics
• Automotive Systems
• Data Science

Artificial Intelligence Dissertations

Most Ph.D. programs require a dissertation. The dissertation takes at least two years to research and write, usually starting in the second or third year of the Ph.D. curriculum. Moreover, many programs require an oral presentation or defense of the dissertation. Some universities give an award for the best dissertation of the year. For example, Boston University gave a best dissertation award to Hao Chen for the dissertation entitled “ Improving Data Center Efficiency Through Smart Grid Integration and Intelligent Analytics .”

A couple of programs require publications, like Capitol Technology , or additional course electives, like LIU . For example, The Ohio State University requires 27 hours of graded coursework and three hours with an advisor for non-thesis path candidates. Thesis-path candidates only have to take 18 hours of graded coursework but must spend 12 hours with their advisors.

Are There Online Ph.D. in Artificial Intelligence Programs?

Officially, the majority of AI Ph.D. programs are in-person. Only one university, Capitol Technology University , allows for a fully online program. This is one of the most expensive Ph.D.s in the field, costing about $60,000. However, it is also one of the most flexible programs. It allows you to complete your coursework on your own schedule, perhaps even while working. Moreover, it allows for either a dissertation path or a publication path. The coursework is fully focused on AI research and writing, thus eliminating requirements for more general courses like algorithms or networks.

One detail you should consider is that the Capitol Technology Ph.D. program is heavily driven by a faculty mentor. This is someone you will need consistent contact with and open communication. The website only lists the director, so there is a significant element of uncertainty on how the program will work for you. But doctoral candidates who are self-driven and have a solid idea of their research path have a higher likelihood of succeeding.

If you need flexibility in your Ph.D. program, you may find some professors at traditional universities will work with you on how you meet and conduct the research, or you may find an alternative degree program that is online. Although a Ph.D. program may not be officially online, you may be able to spend just a semester or two on campus and then perform the rest of the Ph.D. requirements remotely. This is most likely possible if the university has an online master’s program where you can take classes. For example, the Georgia Institute of Technology does not have a residency requirement, has an online master’s of computer science program , and some professors will work flexibly with doctoral candidates with whom they have a close relationship.

What Jobs Can You Get with a Ph.D. in Artificial Intelligence?

Many Ph.D. graduates work as tenure track professors at universities with AI classes. Others work as postdoc research scientists at universities. Both of these roles are expected to conduct research and publish, but professors have more of an expectation to teach, as well. Universities usually have a small number of these positions available. Moreover, postdoc research positions tend to only last for a limited amount of time.

Other engineers with AI-focused-Ph.D.s conduct research and do software development in the private sector at AI-intensive companies. For example, Google uses AI in many departments. Its assistant uses natural language processing to interface with users through voice. Moreover, Google uses AI to generate news feeds for users. Google, and other industry leaders, have a strong preference for engineers with Ph.D.s. This career path is often highly sought by new Ph.D. recipients.

Another private sector industry shifting to AI is vehicle manufacturing. For example, self-driving cars use significant AI to make ethical and legal decisions while operating. Another example is that electric vehicles use AI techniques to optimize performance and power usage.

Some AI Ph.D. recipients become c-suite executives, such as Chief Technology Officers (CTO). For example, Dr. Ted Gaubert has a Ph.D. in engineering and works as a CTO for an AI-intensive company. Another CTO, Dr. David Talby , revolutionized AI with a new natural language processing library, Spark. CTO positions in AI-focused companies often have decades of experience in the AI field.

How Much Do Ph.D. in Artificial Intelligence Programs Cost?

The tuition for many Ph.D. programs is paid through fellowships, graduate research assistantships, and teaching assistantships. For example, Harvard provides full support for Ph.D. candidates. Some programs mandate teaching or research to attend based on the assumption that Ph.D. candidates need financial assistance.

Fellowships are often reserved for applicants with an exceptional academic and research background. These are usually named for eminent alumni, professors, or other scholars associated with the university. Receiving such a fellowship is a highly respected honor.

For programs that do not provide full assistance, the usual cost is about $500 to $1,000 per credit hour, plus university fees. On the low end, Northern Illinois University charges about $557 per credit hour . With 30 to 60 hours required, this means the programs cost about $30,000 to over $60,000 out of pocket. Typically, Ph.D. programs that do not provide funding for any Ph.D. candidates are less reputable or provide other benefits, such as flexibility, online programs, or fewer requirements.

How Much Does a Ph.D. in AI Make?

Engineers with AI Ph.D.s earn well into the six-figure range in the private sector. For example, OpenAI , a non-profit, pays its top researchers over $400,000 per year. Amazon pays its data scientists with Ph.D.s over $200,000 in salary. Directors and executives with Ph.D.s often earn over $1,000,000 in private industry.

When considering working in the private industry, professionals usually compare offers based on total compensation, not just salary. Many companies offer large stock and bonus packages to Ph.D.-level engineers and scientists.

Startups sometimes pay less in salary, but much more in stock options. For example, the salary may be $50,000 to $100,000, but when the startup goes public, you may end up with hundreds of thousands in stock options. This creates a sense of ownership and investment in the success of the startup.

Computer science professors and postdoctoral researchers earn about $90,000 to $160,000 from universities. However, they increase their competition by writing books, speaking at conferences, and advising companies. Startups often employ professors for advice on the feasibility and design of their technology.

Schools with PhD in Artificial Intelligence Programs

Arizona state university.

School of Computing and Augmented Intelligence

Tempe, Arizona

Ph.D. in Computer Science (Artificial Intelligence Research)

Ph.d. in computing and information sciences (artificial intelligence research), university of california-riverside.

Department of Electrical and Computer Engineering

Riverside, California

Ph.D. in Electrical Engineering - Intelligent Systems Research Area

University of california-san diego.

Electrical and Computer Engineering Department

La Jolla, California

Ph.D. in Intelligent Systems, Robotics and Control

Colorado state university-fort collins.

The Graduate School

Fort Collins, Colorado

Ph.D. in Computer Science - Artificial Intelligence Research Area

University of colorado boulder.

Paul M. Rady Mechanical Engineering

Boulder, Colorado

PhD in Robotics and Systems Design

District of columbia, georgetown university.

Department of Linguistics

Washington, District of Columbia

Doctor of Philosophy (Ph.D.) in Linguistics - Computational Linguistics

The university of west florida.

Department of Intelligent Systems and Robotics

Pensacola, Florida

Ph.D. in Intelligent Systems and Robotics

University of central florida.

Department of Electrical & Computer Engineering

Orlando, Florida

Doctorate in Computer Engineering - Intelligent Systems and Machine Learning

Georgia institute of technology.

Colleges of Computing, Engineering, and Sciences

Atlanta, Georgia

Ph.D. in Machine Learning

Northern illinois university.

Dekalb, Illinois

Ph.D. in Computer Science - Artificial Intelligence Area of Emphasis

Ph.d. in computer science - machine learning area of emphasis, northwestern university.

McCormick School of Engineering

Evanston, Illinois

PhD in Computer Science - Artificial Intelligence and Machine Learning Research Group

Indiana university bloomington.

Department of Intelligent Systems Engineering

Bloomington, Indiana

Ph.D. in Intelligent Systems Engineering

Ph.d. in linguistics - computational linguistics concentration, capitol technology university.

Doctoral Programs Department

Laurel, Maryland

Doctor of Philosophy (PhD) in Artificial Intelligence

Offered Online

Johns Hopkins University

Whiting School of Engineering

Baltimore, Maryland

Doctor of Philosophy in Mechanical Engineering - Robotics

Massachusetts, boston university.

College of Engineering

Boston, Massachusetts

PhD in Computer Engineering - Data Science and Intelligent Systems Research Area

Phd in systems engineering - automation, robotics, and control, brandeis university.

Department of Computer Science

Waltham, Massachusetts

Ph.D. in Computer Science - Computational Linguistics

Harvard university.

School of Engineering and Applied Sciences

Cambridge, Massachusetts

Ph.D. in Applied Mathematics

Northeastern university.

Khoury College of Computer Science

Ph.D. in Computer Science - Artificial Intelligence Area

University of michigan-ann arbor.

Electrical Engineering and Computer Science Department

Ann Arbor, Michigan

PhD in Electrical and Computer Engineering - Robotics

University of nebraska at omaha.

College of Information Science & Technology

Omaha, Nebraska

PhD in Information Technology - Artificial Intelligence Concentration

University of nevada-reno.

Computer Science and Engineering Department

Reno, Nevada

Ph.D. in Computer Science & Engineering - Intelligent and Autonomous Systems Research

Rutgers university.

New Brunswick, New Jersey

Ph.D. in Linguistics with Computational Linguistics Certificate

Stevens institute of technology.

Schaefer School Of Engineering & Science

Hoboken, New Jersey

Ph.D. in Computer Engineering

Ph.d. in electrical engineering - applied artificial intelligence, ph.d. in electrical engineering - robotics and smart systems research, cornell university.

Ithaca, New York

Linguistics Ph.D. - Computational Linguistics

Ph.d.in computer science, cuny graduate school and university center.

New York, New York

Ph.D. in Linguistics - Computational Linguistics

Long island university-brooklyn campus.

Graduate Department

Brooklyn, New York

Dual PharmD/M.S. in Artificial Intelligence

Rochester institute of technology.

Golisano College of Computing and Information Sciences

Rochester, New York

North Carolina

Duke university.

Duke Robotics

Durham, North Carolina

Ph.D in ECE - Robotics Track

Ph.d. in mems - robotics track, ohio state university-main campus.

Department of Mechanical and Aerospace Engineering

Columbus, Ohio

PhD in Mechanical Engineering - Automotive Systems and Mobility (Connected and Automated Vehicles)

University of cincinnati.

College of Engineering and Applied Science

Cincinnati, Ohio

PhD in Computer Science and Engineering - Intelligent Systems Group

Oregon state university.

Corvallis, Oregon

Ph.D. in Artificial Intelligence

Pennsylvania, carnegie mellon university.

Machine Learning Department

Pittsburgh, Pennsylvania

PhD in Machine Learning & Public Policy

Phd in neural computation & machine learning, phd in statistics & machine learning, phd program in machine learning, drexel university.

Philadelphia, Pennsylvania

Doctorate in Mechanical Engineering - Robotics and Autonomy

Temple university.

Computer & Information Sciences Department

PhD in Computer and Information Science - Artificial Intelligence

University of pittsburgh-pittsburgh campus.

School of Computing and Information

Ph.D. in Intelligent Systems

The university of texas at austin.

Austin, Texas

Ph.D. with Graduate Portfolio Program in Robotics

The university of texas at dallas.

Erik Jonsson School of Engineering and Computer Science

Richardson, Texas

University of Utah

Mechanical Engineering Department

Salt Lake City, Utah

Doctor of Philosophy - Robotics Track

University of washington-seattle campus.

Seattle, Washington

Ph.D. in Machine Learning and Big Data

GW Online Engineering Programs

• Artificial Intelligence and Machine Learning
• Cloud Computing Management
• Cybersecurity Analytics
• Cybersecurity Policy & Compliance
• Electrical Engineering
• Engineering Management
• Systems Engineering
• Policies & Procedures
• On-Site International Programs
• Artificial Intelligence & Machine Learning (D.Eng.)
• Cybersecurity Analytics (D.Eng.)
• Engineering Management (D.Eng.)
• Systems Engineering (Ph.D.)
• Degrees Offered
• Tuition & Financial Aid
• Student Resources
• Application Process

Apply for Admission

Online Doctor of Engineering in Artificial Intelligence & Machine Learning

We are now accepting applications for the cohort beginning in January 2025.

The application deadline is November 1, 2024

Program Description

The online Doctor of Engineering in Artificial Intelligence & Machine Learning is a research-based doctoral program. The program is designed to provide graduates with a solid understanding of the latest AI&ML techniques, as well as hands-on experience in applying these techniques to real-world problems. Graduates of this program are equipped to lead AI&ML projects and teams in a wide range of industries, including healthcare, finance, and manufacturing. Having developed advanced research skills, graduates are also well-prepared for academic research and teaching roles.

The degree requires completion of eight graduate-level courses (listed below) and a minimum of 24 credit hours of Praxis Research (SEAS 8588). During the research phase, the student writes and defends a research praxis on a topic related to AI&ML. The topic is selected by the student and approved by the research advising committee.

SEAS 6414 Python Application for Data Analytics:  Introduction to Python programming tailored for Data Analytics. This course covers Python’s applications in automating data cleaning, feature engineering, outlier detection, implementing machine learning algorithms, conducting text mining, and performing time series analysis. (3 credit hours)

SEAS 8500 Fundamentals of AI-Enabled Systems:  Operational decomposition for AI solutions, engineering data for algorithm development, and deployment strategies. Systems perspective in designing AI systems. Full-lifecycle of creating AI-enabled systems. Ethics and biases in AI systems (3 credit hours)

SEAS 8505 Applied Machine Intelligence and Reinforcement Learning:  Theory and practice of machine learning leveraging open-source tools, algorithms and techniques. Topics include intelligent model training, support vector machines, deep learning, transformer methods, GANs, and reinforcement learning (3 credit hours)

SEAS 8510 Analytical Methods for Machine Learning:  Mathematical tools for building machine learning algorithms: linear algebra, analytical geometry, matrix decompositions, optimization, probability and statistics (3 credit hours)

SEAS 8515 Data Engineering for AI:  Developing Python scripts to automate data pipelines, data ingestion, data processing, and data warehousing. Machine learning applications with Python including text mining and time series analysis (3 credit hours)

SEAS 8520 Deep Learning and Natural Language Processing:  Fundamentals of deep learning and Natural Language Processing (NLP). Techniques for designing modern deep learning networks using Keras and TensorFlow. NLP topics include sentiment analysis, bag of words, TFIDF, and Large Language Models (3 credit hours)

SEAS 8525 Computer Vision and Generative AI: Explore AI's visual realm. Learn image processing object detection, and models in generative adversarial networks and neural networks. Master tools for creating AI applications in art, design, ethical considerations, and societal impacts of generative AI technology (3 credit hours)

SEAS 8599 Praxis Development for AI & Machine Learning:  Overview of research methods. Aims and purpose of the praxis. Development of praxis research strategies, formulation, and defense of a praxis proposal (3 credit hours)

SEAS 8588 Praxis Research for D.Eng. in AI & Machine Learning:  Research leading to the degree of Doctor of Engineering in AI and Machine Learning (24 Credit Hours)  

Classroom courses last 10 weeks each and meet on Saturday mornings from 9:00 AM—12:10 PM and afternoons from 1:00—4:10 PM (all times Eastern). All classes meet live online through synchronous distance learning technologies (Zoom). All classes are recorded and available for viewing within two hours of the lecture. This program is taught in a cohort format in which students take all courses in lockstep. Courses cannot be taken out of sequence, live attendance at all class meetings is expected, and students must remain continuously enrolled. Leaves of absence are permitted only in the case of a medical or family emergency, or deployment to active military duty.  Please see below for the dates of our upcoming cohort.

No classes on  Memorial Day and Fourth of July weekends 

To proceed to the research phase, students must earn a grade point average of at least 3.2 in the eight classroom courses, and no grade below B-. Students are then registered for a minimum of 24 credit hours of SEAS 8588 Praxis Research: 3 ch in Fall 2025 (Session 2), 9 ch in Spring 2026, 3 ch in Summer 2026, and 9 ch in Fall 2026. Throughout the research phase, students develop the praxis under the guidance of a designated faculty advisor. Faculty research advisors are assigned by the program office and meet individually with students every two weeks.

Sample research areas are listed below:

•    Developing algorithms and methods that can explain how AI systems reach their decisions or predictions, making them more transparent and trustworthy •    Investigating how reinforcement learning can improve robotic performance and control, particularly in complex environments •    Examining how to ensure that AI systems are fair and unbiased in their decision-making, particularly in areas such as hiring, lending, and criminal justice •    Developing more advanced natural language processing models and algorithms that can understand and interpret human language more accurately and effectively •    Investigating how to apply transfer learning techniques to improve the performance of AI systems in new and different domains, with less data and less training time 

Tuition is $1,750 per credit hour for the 2024-2025 year and is billed at the beginning of each semester for the courses registered during that semester. A non-refundable tuition deposit of $995, which is applied to tuition due the first semester, is required when the applicant accepts the offer of admission.

Admissions Process

• Bachelor’s and master’s degrees in engineering, applied science, business, computer science, or a related field from accredited institutions.
• A minimum graduate-level GPA of 3.2
• Capacity for original scholarship.
• TOEFL, IELTS, Duolingo, or PTE scores are required of all applicants who are not citizens of countries where English is the official language.  Check our  International Students Page  to learn about the SEAS English language requirements and exemption policy. Test scores may not be more than two years old.

Note: GRE and GMAT scores are not required

Please note that our doctoral programs are highly selective; meeting minimum admissions requirements does not guarantee admission.  

• Attach up-to-date Resume 
• Attach Statement of Purpose – In an essay of 250 words or less, state your purpose in undertaking graduate study at The George Washington University. Describe your academic objectives, research interests, and career plans. Discuss your qualifications including collegiate, professional, and community activities, and any other substantial accomplishments not mentioned.
• Online Engineering Programs The George Washington University 170 Newport Center Drive Suite 260 Newport Beach, CA 92660

Normally, all transcripts must be received before an admission decision is rendered for the Doctor of Engineering program. 

Register for the next Information Session

Live via Zoom Thu. September 26th, 7:00 pm Eastern Register and Join the Webinar

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Postdoctoral Researcher, Artificial Intelligence (PHD) | Chercheur postdoctoral, Intelligence artificielle (PHD)

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• Perform research to advance the science and technology of intelligent machines by enhancing their perception of the world through multi-modal input | Effectuer des recherches pour faire progresser la science et la technologie des machines intelligentes en améliorant leur perception du monde grâce à des apports multimodaux
• Perform research that enables such machines to generate visual data and reason about the world | Effectuer des recherches permettant à ces machines de générer des données visuelles et de raisonner sur le monde
• Contribute research that can be applied to Facebook product development | Contribuer aux recherches pouvant être appliquées au développement des produits de Facebook.
• Currently has or is in the process of obtaining a PhD degree or completing a postdoctoral assignment in the field of Computer Science or similar | Être titulaire d'un doctorat, ou être en voie de l'obtenir, dans le domaine des sciences informatiques ou dans un domaine semblable, ou mener des travaux postdoctoraux dans ces domaines
• Publications in Machine Learning, robotics, computer vision, AI, computer science, statistics, applied mathematics, data science, or related technical fields | Publications dans le domaine de l'apprentissage automatique, de la robotique, de la vision par ordinateur, de l'IA, des sciences informatiques, des statistiques, des mathématiques appliquées, de la science des données ou dans d'autres domaines techniques pertinents
• Experience solving analytical problems using quantitative approaches | Expérience dans la résolution de problèmes analytiques à l'aide d'approches quantitatives
• Experience manipulating and analyzing data from varying sources | Expérience en manipulation et en traitement de données provenant de différentes sources
• Experience communicating research | Expérience en communication des recherches
• Coding experience in C++, Python, or other similar language | Expérience de programmation en C++, en Python ou dans un autre langage semblable
• Must obtain work authorization in country of employment at the time of hire and maintain ongoing work authorization during employment | Doit obtenir un permis de travail dans le pays où se trouve l'emploi à la date d'embauche et maintenir ce permis pendant la durée de l'emploi
• Research and software engineer experience demonstrated via an internship, work experience, coding competitions | Expérience de recherche et de génie logiciel confirmée par un stage, l'expérience professionnelle, la participation à des compétitions de programmation

Perks and Benefits

Health and wellness.

• Health Insurance
• Health Reimbursement Account
• Dental Insurance
• Vision Insurance
• Life Insurance
• Short-Term Disability
• Long-Term Disability
• FSA With Employer Contribution
• HSA With Employer Contribution
• Fitness Subsidies
• On-Site Gym
• Mental Health Benefits

Parental Benefits

• Birth Parent or Maternity Leave
• Non-Birth Parent or Paternity Leave
• Fertility Benefits
• Adoption Assistance Program
• Family Support Resources

Work Flexibility

• Flexible Work Hours
• Remote Work Opportunities
• Hybrid Work Opportunities

Office Life and Perks

• Commuter Benefits Program
• Casual Dress
• Happy Hours
• Some Meals Provided
• Company Outings
• On-Site Cafeteria
• Holiday Events

Vacation and Time Off

• Paid Vacation
• Unlimited Paid Time Off
• Paid Holidays
• Personal/Sick Days
• Leave of Absence

Financial and Retirement

• 401(K) With Company Matching
• Company Equity
• Performance Bonus
• Relocation Assistance
• Financial Counseling

Professional Development

• Learning and Development Stipend
• Promote From Within
• Mentor Program
• Shadowing Opportunities
• Access to Online Courses
• Lunch and Learns
• Internship Program

Diversity and Inclusion

• Diversity, Equity, and Inclusion Program
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PM Modi pushed us to continue making, designing in India: Sundar Pichai

Google's ceo sundar pichai stated that the pm highlighted artificial intelligence (ai) and asked the tech giants to do more in terms of ai so that "it benefits people of india." .

Listen to Story

• PM Modi meets global tech CEOs in New York
• PM Modi encourages AI applications in key sectors, says Sundar Pichai
• Sundar Pichai emphasised AI benefits for India

After Prime Minister Narendra Modi held a roundtable meeting of prominent Chief Executive Officers (CEOs) of global tech giants in New York, Google's CEO Sundar Pichai stated that the PM highlighted artificial intelligence (AI) and asked the tech giants to do more in terms of AI so that "it benefits people of India."

Google CEO @sundarpichai after meeting Prime Minister @narendramodi : - PM Modi has pushed us to continue to making in #India and designing in India; - He wants to make sure that ultimately #AI is there to benefit the people of India; - He is challenging us to do more in termsâ€æ pic.twitter.com/ZNIMmX7HQ7 — Kanchan Gupta 🇮🇳 (@KanchanGupta) September 23, 2024

He highlighted PM Modi’s forward-thinking approach to artificial intelligence, noting, stating, "He’s really thinking about how AI can transform India in ways that benefit its people. He challenged us to explore applications in healthcare, education, and agriculture, while also focusing on the nation’s infrastructure — whether it’s data centres, power, or energy — to support India’s transition."

Pichai also outlined Google's commitment to AI expansion in India, saying, “We are proud to be partnering with India. We are making significant investments in AI here and look forward to doing more. Several programs and partnerships are already in place."

He added that PM Modi has consistently pushed them to do more for India, and now the challenge extends to AI.

"He has a clear vision of the opportunities AI presents but remains focused on ensuring that AI serves the people of India. His leadership is all about making sure AI works for the greater good," Pichai concluded.

The meeting was held at the Lotte New York Palace Hotel on Sunday during the second day of PM Modi's three-day US visit. IBM’s CEO Arvind Krishna and Noubar Afeyan, the chairman of Moderna, amongst others attended the meeting.