Programme Thesis
The AIMS Google DeepMind Scholarship funds a fully residential one-year Master's in Mathematical Sciences (AI for Science stream) at AIMS South Africa, aiming to equip African students with AI and machine learning skills to solve real scientific problems. It exists to bridge the gap between mathematical sciences and AI, fostering a new generation of African researchers who can apply computational methods to pressing scientific challenges.
Selection Criteria
- African citizenship and residence in Africa at time of application
- Completed 4-year undergraduate degree or 3-year degree with Honours by August/December 2025
- Undergraduate degree in Computer Science, Engineering, Mathematics, Statistics, Physics, or a discipline with strong computational/mathematical component
- Enrolling in a Master's programme (must not have held previous AIMS scholarship)
- Passion for mathematics, AI, and machine learning (demonstrated in motivational letter and application)
- Performance on mathematics questions and coding problem in online application (not an exam, but shows problem-solving approach)
- Quality of representative examples of work in mathematical sciences
- Motivational letter (~500 words) that clearly articulates alignment with AI for Science and personal research goals
- Interview performance (final round, May 2026)
Past Winners / Cohort Profiles
The programme targets African students with strong mathematical and computational backgrounds, often from STEM fields like computer science, physics, or engineering. Past cohorts include individuals who have completed undergraduate degrees with Honours and demonstrate a clear passion for applying AI to scientific problems. Named examples are not provided on the page, but typical winners are early-career researchers with a track record of independent projects or research in AI/ML applications to science.
Ideal Candidate Fingerprint
The platonic ideal applicant is an African citizen with a strong undergraduate degree in a quantitative field (e.g., mathematics, computer science, physics), a demonstrated passion for AI and machine learning through projects or research, and a clear vision for using AI to solve a scientific problem. They should be able to showcase mathematical rigor and coding ability, and be ready for a fully residential, intensive one-year Master's programme.
Recommended Framing
Eniola Olutogun should frame his application around his unique multi-domain computational research that directly embodies the AI for Science mission: his CCT addiction model uses Bayesian MCMC and ODEs to solve a neuroscience problem, his TOPOLOGIX work applies protein language models to drug resistance, and his hERG topology study uses topological data analysis for cardiotoxicity prediction. Emphasize his Nigerian citizenship, independent research track record (sole-authored preprints, pre-registered studies), and upcoming M.Sc. enrollment to show he is an ideal candidate for this LMIC-track, early-career fellowship that values mathematical rigor and AI-driven scientific discovery.
Watch Out
None. Eniola meets all eligibility criteria: African citizen (Nigerian), resides in Africa (currently in Germany for M.Sc. but likely still considered African resident? Need to confirm residence at time of application), has a 4-year B.Pharm degree (strong computational component), is enrolling in a Master's (HPI/Potsdam), and has not held a previous AIMS scholarship. His B.Pharm CGPA of 5.1/7.0 (German 1.9) is strong, and his research output is exceptional for an independent researcher.