Medical Fellow - Human Frontier Collective
Medical fellows apply clinical expertise to design scenarios, evaluate generative AI decision-making, and provide structured feedback for safer, more accurate healthcare systems. The role requires an MD or DO, board certification, strong clinical reasoning and writing skills, and a relevant medical specialty.
About the job
Responsibilities
- Collaborate on high-impact projects with AI labs and platforms.
- Design complex clinical scenarios and evaluate model decision-making for safety and accuracy.
- Shape AI reasoning frameworks through structured, example-driven feedback.
- Collaborate with research teams to co-author technical reports and research papers.
Requirements
- Medical degree required (MD or DO) with board certification.
- Open to residents, practicing clinicians, and candidates with extensive clinical experience.
- Background in internal medicine, emergency medicine, radiology, surgery, psychiatry, or a related field.
- Strong clinical reasoning and writing skills.
- Ability to assess complex, nuanced, or edge-case scenarios.
- Detail-oriented, innovative, and collaborative mindset.
- Prior AI experience is a plus but not required.
Compensation and Benefits
- Fully remote, independent contractor opportunity with an estimated six-month duration and potential extension.
- Flexible schedule with 10–40 hour work weeks.
- Project pay varies based on project, scope, skill set, and location.
- Opportunities for professional development, advisory work, research collaboration, and co-authored publications.
- Participation in an interdisciplinary global network focused on responsible AI.
Application Process
- Applications are reviewed on a rolling basis.
- Selected candidates complete a brief domain-expertise challenge.
- Candidates participate in an interview covering research experience, professional background, and mission alignment.
Skills
Clinical Reasoning, Medical Diagnosis, Medical Writing, Artificial Intelligence, Generative AI, Model Evaluation, Safety Evaluation, Research Publications
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