Programme Thesis
The ISSER Pre-Doctoral Fellowship funds a one-year, applied development research placement at the University of Ghana, specifically supporting CGIAR's Standing Panel on Impact Assessment (SPIA) work on agriculture, natural resources, and food systems. It exists to build a pipeline of early-career researchers from around the world into doctoral studies and rigorous impact evaluation practice in African development contexts.
Selection Criteria
- Master's degree in economics, agricultural economics, or a related field (required)
- Strong quantitative and analytical skills (required)
- Experience in data collection and research (required)
- Demonstrated interest in agriculture, natural resources, and food systems in developing countries (required)
- Good communication and teamwork skills (required)
- Knowledge of impact evaluation (advantageous)
- Academic qualifications, research experience, and motivation for doctoral studies (selection emphasis)
- Ability to produce at least two technical papers during the fellowship (implied)
- Fit with SPIA's research agenda and mentorship structure (implied)
Past Winners / Cohort Profiles
The page does not list past winners. Based on the programme's focus, past fellows are likely early-career researchers (typically recent master's graduates) with strong econometrics or quantitative social science training, prior fieldwork or data collection experience in developing countries, and a clear trajectory toward a PhD in economics or development-related fields. They are often affiliated with African universities or research institutions, and have experience with household surveys, RCTs, or quasi-experimental methods.
Ideal Candidate Fingerprint
The ideal applicant is a recent master's graduate in economics or agricultural economics with strong quantitative skills (e.g., econometrics, Stata/R), hands-on experience in field data collection and impact evaluation, and a demonstrated commitment to development research in African agriculture or food systems. They are motivated to pursue a PhD and can work collaboratively within a research team, producing policy-relevant technical papers under mentorship.
Recommended Framing
For Eniola, the strongest angle is to leverage his quantitative modeling and data science expertise as a transferable asset for development research, specifically by proposing to apply his dynamical-systems and machine-learning methods to agricultural or food-system impact evaluation. However, his current research lines (CCT, TOPOLOGIX, neurocascade, etc.) are biomedical and not directly aligned; the most relevant is his experience with Bayesian calibration and complex ODE models, which could be framed as advanced quantitative skills for analyzing agricultural systems or evaluating interventions. He should explicitly connect his computational modeling background to the fellowship's focus on impact evaluation, perhaps by proposing to use agent-based or systems-dynamics models to simulate agricultural interventions, and emphasize his African background and interest in development challenges.
Watch Out
- The fellowship requires a master's degree in economics, agricultural economics, or a related field; Eniola's M.Sc. in Digital Health is not yet completed (enrolled for Winter 2026/27) and is not in a directly related field, which may be a hard eligibility barrier.
- His research experience is heavily biomedical and computational, with no demonstrated experience in agriculture, natural resources, food systems, or impact evaluation.
- The fellowship is based in Ghana and requires physical presence; Eniola is currently in Germany for his M.Sc., which may pose logistical challenges.
- Only one fellowship position is available, making competition intense and fit critical.
Research History
2026-08-04 20:10 · low confidence
2026-07-31 17:10 · medium confidence