Oxford Schmidt AI in Science Faculty Fellowship

Objectives: To identify and support exceptional early-career faculty based at Indian universities who are working on using AI to accelerate progress in other scientific fields. This Fellowship program is designed for faculty working at either the Assistant or Associate Professor level. This programme aims to provide the faculty with the tools and training needed to apply state-of-the-art AI and machine learning methods for maximum impact in their particular area of scientific research. The programme will enable the faculty to develop and apply AI techniques across engineering, and the natural and mathematical sciences while maintaining their positions at their home institutions in India and establish strong cross-disciplinary collaborative links with academic colleagues in Oxford.

Note, we do not expect prospective faculty to be experts in AI and/or machine learning.

We expect that they are leading researchers in a scientific domain (of those outlined below) but should have identified an opportunity where AI and/or machine learning could feasibly lead to a step-change in their domain.

Please note these faculty fellowships are open to academics working in one (or more) of the following three priority application areas of AI:

1. Climate Change, Environment, and Biodiversity.
2. Food and Water Security.
3. STEM underpinning Biomedical Research.

We note that projects working directly on medical data or towards clinical outcomes, including projects involving patient records and clinical trials, are not eligible through this scheme.

Eligibility:

The applicants should: 

● Be an Indian Citizen and a Resident of India.
● Hold a PhD degree.
● Be currently employed at a university or an academic institute in India as either an Assistant Professor or Associate Professor.
● Be within the first 6 years of their current faculty appointment.
● Have an active research program on using AI to accelerate progress in scientific fields OR have a promising research idea to demonstrate how AI can embellish scientific progress, while also considering potential ethical implications.

Assessment criteria

• Strong research track record appropriate to the career stage of the applicant
• The underpinning applied science is internationally leading, with the application of AI/ML techniques appropriate and likely to lead to a step-change in the application domain
• Application alignment with the three priority application areas (stated above)
• Appropriate level of understanding of how AI techniques might be applied in order to progress the research area
• Clear demonstration of how the training component will benefit the applicant, their research, and their career
• Clear demonstration of how the impact of their research will benefit the wider community
• Evidence of how the applicant will benefit from being part of a cohort and the ability to demonstrate what makes them a good fit for the programme

Fellowship Structure

The new Oxford Schmidt Africa-India AI in Science Faculty Fellowship Programme (AI2-Ox SFF) will build on the existing Schmidt AI in Science Postdoctoral Fellowship, which has already welcomed 25 Fellows. The extension specifically targets early-career Indian faculty in permanent positions at the Assistant or Associate Professor level. The aim of this programme is to advance research using cutting-edge AI tools to address a critical gap in research development. Each fellowship will last three years and provide the tools and training needed to apply state-of-the-art AI and machine learning methods in each researcher’s particular area of scientific interest. Throughout the duration of the Fellowship programme, the Fellow will have a research host (an academic) within an Oxford department who will act as an informal mentor and will host the Fellows within their research group during year 2. The selection panel will help facilitate the matching process between Fellows and a suitable research host. So, we ask that interested candidates do not contact Oxford faculty for research host-related inquiries throughout the application process.

The AI2-Ox SFF programme will adopt a unique “1+1+1” year structure:

Year 1: The Fellows will be provided funding (up to their 0.5 Full-Time Equivalent (FTE) salary) that could be used for: (a) a teaching buyout, (b) an administration buyout, and (c) research support (e.g. hiring a research assistant), in their home institution. There will be a two-week visit to Oxford to meet the collaborating group and research host and to further develop research plans. During this visit, the Oxford Research Software Engineering group will provide training on research software engineering (OxRSE), and, during the second week, we will hold a group RSE-project week; during this visit, a Training Needs Analysis will be conducted with the Fellows to put in place a plan for their AI/ML and
professional skills training throughout the Fellowship.

Year 2: Fellows will be seconded to Oxford for the whole academic year, with a 1.0FTE buyout of teaching and administration in the home institution. Fellows will be embedded in their host research group to conduct their own research programme with support from their research host. Fellows will also be associated with an Oxford college, each a broad community of academics in Oxford, to expand their networks and contribute to university research and engagement activities. The following four Oxford colleges are partnering in this fellowship programme, Linacre, Mansfield, Reuben and Somerville. Selected candidates will receive further details regarding college allocation and facilities available in colleges at a later stage in the selection process. There will likely be opportunities for the Fellows to co-supervise Masters and PhD students. In addition to their relationship with the academic host, the Fellows will be encouraged to collaborate with other faculty at Oxford and beyond. Fellows will undertake tailored AI/ML training as well as a host of relevant other professional development courses. Fellows and their home institutions will have access to the online resources developed by the University’s Next Generation Research Computing Group throughout the fellowship. The Fellows will attend academic leadership training, and supervision & management training. Funds will be available for Fellows to attend conferences.

Year 3: The Fellows will be provided funding (same as year 1) that could be used for: (a) teaching buy out, (b) administration buy-out, and (c) research support, in their home institution. The Fellows will continue to collaborate with colleagues in Oxford and attend online training courses as needed.
Fellows will benefit from:

• Bespoke training in AI and machine learning methods
• Research software engineering training and support from the OxRSE group
• Mentoring from leading Oxford researchers
• Career and professional development support
• Opportunities to build strong academic networks

The programme will facilitate knowledge and skills sharing between Oxford and institutions in India and Africa, by enabling researchers to engage with the university while maintaining their positions at their home institutions.

Application process

Stage 1

The application portal opens on 28 March and closes on 28 April. The information required at this stage will be:

• CV (7 pages maximum, Calibri 11pt font, 2cm margins, including a list of academic publications and teaching commitments)
• Brief research proposal, clearly setting out the research project you wish to pursue, including how your existing or proposed approach will find application within the three priority application areas listed in the eligibility criteria and why this use of AI/ML will result in novel insights and impact. Please specify clearly which of the three priority areas is best aligned with your research interests. Your research proposal should include key summaries that can be used for communication with a non-scientific audience (max. 300 words).
• Contact details of two referees (name, title, email, work address). These referees should be people who have directly worked with you in an academic setting in the past, in either a supervisory capacity or on a collaborative research project.
• Contact details of Head of Department (or equivalent). Note, that this individual will only be asked to confirm their support in Stage 1 (i.e. pre-shortlisting); if the application gets through to the shortlisting phase, we will ask them to write a letter of support.
• Any extenuating circumstances (optional) please outline any interruptions to your research/career which you would like the selection panel to be aware of; these might include caring duties.

Stage 2 (for shortlisted candidates only)

The application portal opens on 20 May and closes on 3 June. The information required at this stage will be:

• Statement of purpose explaining why your existing research and future career plan makes you a good fit for the Schmidt Faculty Fellowship Programme (max. 1000 words).
• Detailed research proposal clearly setting out the research project you wish to pursue, including how your existing or proposed approach will find application within the three priority application areas listed above, and why this use of AI/ML will result in novel insights and impact. Please provide a detailed research proposal for a scientific audience (max. 2000 words).
• Letter of support from the Head of Department, or equivalent (at the institute where the applicant is currently based).
• Two samples of written work (published or working papers) within the last 5 years that are relevant to this fellowship. For each piece of work, provide a short statement explaining its significance in broad terms and its relevance to this fellowship (max. 100 words for each written work). For any co-authored work, please also state your contributions to the paper (max. 100 words for each written work).
• Training plan providing an overview of any AI-related or professional skills you will need to acquire or further develop in order for you to succeed in your planned research (max. 500 words).
• Statement on ensuring wider benefits of this fellowship explaining the approaches you will take to maximise the impact of your work and ensure equitable take-up of your research (max. 200 words).

Applicants who are shortlisted after stage 2 will be invited to interview. Interviews will be held online in July.

Applicants who are shortlisted after stage 2 will be invited to interview. Interviews will be held online on 30th June & 1st July 2025.

Your application will be reviewed by a multidisciplinary panel of academic researchers, and decisions will be based solely on how you demonstrate that you meet the selection criteria stated above.  Short-listed candidates will be interviewed as part of this process. Please note that there may not be experts in your scientific area or the specific AI techniques you plan to use on the panel, so please ensure that your methods and the science behind them are clearly explained.