Global Early-Career Short Research Fellowship: AI in Science and Open Hardware for Lab Automation

Funding to support short term high-impact visits to Imperial for early career researchers based in Low and Middle Income Countries, with a topical focus on AI in Science or Open Hardware for Lab Automation.

These length of the visit should be a minimum of 4 weeks, and a maximum of 8 weeks. To take place in Spring 2026.

The fund will provide:

• Subsistence grant: £950 per week to cover food, accommodation and other necessary expenses.
• Return economy class flights
• Payment for standard visitor visa
• Contribution towards costs for travel/medical insurance

The 2025-26 cycle will support up to 5 researchers.

Participants must:

• Be within 8 years of PhD or 6 years of first academic appointment, excluding career breaks.
• Be a passport holder and be a permanent resident of a Least Developed (LDC) or Lower Middle Income Country (LMIC), as specified by the OECD ODA Recipients List. Please note, this does not include Upper Middle Income Countries. *
• Be currently based at an institution in an LDC or LMIC country.
• Have a Letter of Support from an academic host supervisor at Imperial. The supervisor should ensure that the Letter of Support is signed by the Head of Department. 
• Have a Letter of Recommendation from their own institution.

You are not eligible for this opportunity if you:

• Hold dual British citizenship
• Are a permanent resident of a country that is not considered a Least Developed or Lower Middle Income Country
• Are currently based at a non LDC/LMIC institution
• Are a current doctoral (PhD) student 

*If you have any queries relating to eligibility, please get in contact.

The research focus of the visit must fit within the scope outlined below:

1. AI in Science – for definitions of this see eligibility conditions below – this visit would be devoted to disrupting normal scientific practice by using AI tools.
2. Open Hardware for Lab Automation - Lab automation will be understood broadly to include physical automation of experimental workflows; open‑source (open‑science) laboratory hardware; computational infrastructure that directly supports automation; automation of low-throughput experiment as well as self‑driving labs (closed‑loop autonomous experimentation).

A short report will be required at completion.

If you have any questions about the research remit, please get in touch: globaldevelopment@imperial.ac.uk 

Application process

Applicants must be hosted by an Imperial academic for the duration of their stay.

Applicants are responsible for identifying their own host academic using the university directory and other resources. A list of all faculties and departments can be found here.

It is at the discretion of the Imperial academic as to whether they would like to host you. We encourage preexisting collaborators to explore opportunities for visiting researchers.

All eligible applications will be reviewed by a selection committee at Imperial and notified via email.

Applicants must complete the online application form and send the following supporting documentation to globaldevelopment@imperial.ac.uk before the closing date (12th December).

• 2-page academic CV
• Host support letter (bench-fee waiver, workspace/lab access, induction/supervision plan)
• Home institution support letter (status, support of the visit)

Eligible costs: Subsistence (to cover accommodation, food, subsistence), consumables (cap ≤10%), small equipment, visa/ETA and health/ travel insurance.

Ineligible costs: salary, bench fees, overheads.

Host departments are expected to waive bench fees and confirm desk/lab access in their support letter.

Researchers may require an ATAS certificate for the visit. Please check with your host supervisor whether this is a requirement. 

Here ‘AI’ is interpreted very broadly, e.g.: including topics in Bayesian Inference and Robotics; ‘Science’ covers any typical topic in Natural Science and Engineering (Epidemiology, Biology and basic science in biomedicine are included but clinical medical themes are not covered, including conventional medical imaging). Example topics include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML for turbine design; satellite imaging to predict disease risk; and Astrostatistics. These posts are not suitable for research into generic AI with general application: candidates must be aiming to substantially advance a particular area of science. Applicants could view themselves as AI researchers tackling a particular piece of Science or Science researchers using AI to transform their area. A deep knowledge of AI is not a precondition for this fellowship: only an appreciation of the need for AI and a willingness for skill acquisition in AI. 

We do include epidemiology but outside this no: the grant’s principal orientation is towards the natural sciences and engineering. 

‘Science’ covers any typical topic in Natural Science and Engineering (Epidemiology, Biology and basic science in biomedicine are included but clinical medical themes are not covered, including conventional medical imaging). We are pleased to support medical research that attempts to characterise a biological system/process including a pathophysiological process/state. Our centre does not seek to support translational medical research or the development of therapeutic technologies. A proposal can certainly connect to therapy and technology, but this should not be the principal objective of the fellowship.

Yes! Deep knowledge of AI is not a precondition for applying -- the fellowship can help you pivot into acquiring AI skills to advance your disciplinary area. You might want to pick your host and design your training program accordingly. 

Yes! Deep knowledge of the Scientific area is not a precondition for applying -- the fellowship can help you pivot into acquiring deeper subject area expertise. Please pick only one area to target. You might want to pick your host and design your training program accordingly.

Yes! Critically you should view this fellowship as an opportunity to pick one application area and pivot into gaining a much deeper mastery of it -- you cannot cover multiple application areas in different fields within the fellowship. You might want to pick your host and design your training program accordingly. 

Yes! You would need to cover how the AI you do is somewhat distinctive and not very widespread in the field. 

In some scientific subfields there are now very well-established AI tools, and the use of these particular AI tools could be considered ‘completely routine,’ ‘standard practice appearing in almost all papers within the scientific subfield’ or extremely widely used’: these fellowships are broadly intended to unlock new areas of science through AI. While we appreciate that this is a grey area, we ask candidates to clarify if they are proposing a different set of AI tools to those that are very well established (or developing new AI tools) with the goal of unlocking new science; or taking some kind of distinctive approach; or that their approach is not very standard practice. A particular use of AI that is standard practice in one subfield might be rare in another (perhaps close) subfield: for any given AI approach our fellowship favours the application of an AI approach to a subfield in which it is more rarely used.