← GovAI Research Fellowship 2026 HIGH Neuropharm/CCT
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GovAI Research Fellowship 2026 ·
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MEDIUM confidence Researched 2026-07-28 13:15 · profile: researcher
The GovAI Research Fellowship funds independent researchers to produce high-impact policy-relevant research on AI governance, helping policymakers and organizations navigate advanced AI risks. It exists to build a global community of experts who can shape responsible AI development through rigorous analysis, publications, and direct advisory work.
- Demonstrated experience conducting high-quality research (track record of impactful publications, preprints, or reports) - Expertise in AI governance or a closely related discipline (e.g., AI safety, computational neuroscience, pharmacology, dynamical systems) - Strong interest in shaping the future of AI responsibly (alignment with GovAI's mission) - Ability to work independently while collaborating with other researchers - Interest in mentoring junior researchers - No formal degree requirements; candidates from academic, government, industry, and civil society backgrounds encouraged - Likely evaluation: clarity of research agenda, feasibility, policy relevance, novelty, and fit with GovAI's research areas (AI risk management, governance, safety, economics, geopolitics, threat modeling, strategic policy)
The page does not list specific past winners. Typical GovAI Research Fellows are early-to-mid-career researchers with PhDs or equivalent experience in AI safety, governance, or technical AI fields, often from top universities (Oxford, Cambridge, MIT, Stanford) or policy organizations. Archetypes: technical AI safety researchers pivoting to governance, social scientists studying AI risk, or policy analysts with strong quantitative backgrounds. Named examples not available on this page.
A researcher with a strong publication record in AI governance or a directly relevant technical field (e.g., AI safety, computational neuroscience, pharmacology), a clear independent research agenda linking their expertise to AI policy, and demonstrated ability to produce policy-relevant outputs. They should be comfortable advising governments and mentoring junior researchers, with a global perspective and collaborative mindset.
Eniola should frame their CCT model and neurocascade work as foundational for AI governance of neurotechnology and AI-driven drug discovery, arguing that understanding reward-memory encoding and brain-circuit simulation is critical for regulating AI systems that interface with human cognition. Their independent, multi-domain computational research (protein ML, dynamical systems, addiction neuroscience) positions them uniquely to advise on AI risks in pharmacology and neuroscience, a niche GovAI likely values. Emphasize the policy implications of their pre-registered, Bayesian-calibrated models and their ability to translate technical findings into actionable governance recommendations.
The fellowship is for experienced researchers; Eniola is pre-PhD (enrolled in M.Sc.) and independent, which may be seen as less established. The focus is explicitly on AI governance, not computational neuroscience or pharmacology per se—Eniola must clearly connect their work to AI risk and governance. Visa sponsorship in the US is exceptional; UK placement may be more feasible. No formal degree requirement helps, but competition is high from PhD-holding applicants.
2026-07-28 09:43 · medium confidence