About Mind Moves
Mind Moves is a women-owned Washington, D.C.-based firm that helps government and business partners navigate digital transformation using "human-in-the-loop" AI. Our expert team has delivered responsibly developed AI products that drive millions in impact across agencies like the National Institutes of Health (NIH).
Program Overview
The National Library of Medicine (NLM) is planning to launch Biomedical AI Challenges — a structured prize competition program designed to catalyze innovation in AI-powered tools for biomedical research infrastructure. The program comprises two parallel challenge competitions (total prize pool: $500,000) focused on: (1) improving AI-enhanced semantic search across PubMed/PMC, and (2) establishing foundational data interoperability by mapping raw, cohort-specific dbGaP study variables directly to precise, standardized international vocabularies/ontologies (such as LOINC, RxNorm, and the UMLS Metathesaurus).
Position Summary
The Biomedical Subject Matter Expert (SME) serves as a senior scientific advisor and technical authority to provide expert guidance on evaluation framework development, benchmark dataset validation, and scientific review panel activities. The Biomedical SME contributes meaningfully to shaping the scientific integrity and rigor of both challenge tracks.
Key Responsibilities
Evaluation Framework Development
Lead or co-lead the development of technically rigorous evaluation frameworks and scoring rubrics for one or both challenge tracks.
Draft descriptor anchors, criterion weights, and reviewer guidance documentation; advise on handling of scoring ties and edge cases.
Provide domain expertise to support the recruitment and vetting of independent expert reviewers, ensuring coverage of relevant disciplines (e.g., information retrieval, NLP, scientific bibliometrics, federated learning, biomedical informatics).
Benchmark Data and Technical Review
Provide expert review and validation of benchmark and reference datasets developed for both challenge tracks, including relevance-judged query sets (Challenge 1) and cross-ontology precision mapping (Challenge 2).
Review dataset documentation for scientific accuracy, provenance disclosure, and methodological soundness prior to participant release.
Advise on hidden test set design to ensure evaluation rigor.
Submission Review
Serve as an evaluator during the expert review phase, ensuring adherence to scoring rubrics and structured deliberation protocols.
Contribute to the Review Panel Report, including narrative summaries of reviewer deliberations and recommendations for award recipients.
Required Qualifications
Advanced degree (Ph.D., M.D., or equivalent) in biomedical informatics, computational biology, biomedical sciences, information science, or a closely related field.
Minimum 8 years of progressive experience in biomedical research, health IT, or a related domain, with demonstrated expertise in at least one of the following: biomedical literature analysis, natural language processing applied to health/life sciences, information retrieval, or controlled-access biomedical data governance.
Demonstrated experience contributing to evaluation framework design, scientific review panels, or prize competition programs.
Familiarity with NLM resources (PubMed, PMC, dbGaP, UMLS, MeSH) and their role in biomedical research infrastructure.
Strong written communication skills; ability to produce scientifically rigorous, publication-quality documentation.
Ability to obtain a Public Trust background investigation designation as required for access to HHS/NLM systems.
Preferred Qualifications
Prior experience with federal challenge competitions (e.g.,
Challenge.gov
, COMPETES Act programs) or NIH-funded research programs.
Expertise in AI/ML methods applied to biomedical literature, genomics, imaging, or clinical data.
Familiarity with federal data governance frameworks including FISMA, NIST SP 800-53, and FedRAMP requirements.
Interview Process
Priority deadline for application is September 6th, 2026, and we look to fill these roles as soon as possible. If interested, please submit your application today! We expect the process to include a short hiring exercise followed by 1 20-30 min interview for final candidates.