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developing next-generation AI methods for healthy climate adaptation. The position will focus on building and evaluating foundation models for large-scale spatiotemporal health and environmental data. Our team
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. ● Contribute to open-source code and reproducible pipelines. Basic Qualifications ● PhD (completed or near completion) in Statistics, Biostatistics, Data Science, Computer Science or a closely related field
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, neural data analysis, or modeling neural activity from large-scale recordings. Ability to work effectively in a collaborative research environment and communicate technical work clearly. Additional
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economists, physicians, and statisticians—on projects that bridge methods, policy, and practice. Position Description: This role will involve intensive analysis of claims data and related large administrative
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economists, physicians, and statisticians—on projects that bridge methods, policy, and practice. Position Description: This role will involve intensive analysis of claims data and related large administrative
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track record of peer-reviewed publications commensurate with career stage. Additional Qualifications Prior experience with one or more of: ● Health claims data, EHRs, or other large-scale health
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. Experience with cell state modeling from large-scale perturbation datasets, including Perturb-seq or related data. Experience with multimodal modeling for protein function or cellular state prediction
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possible. Basic Qualifications PhD in computer science, statistics, electrical engineering, applied mathematics, computational biology, or a related quantitative field required by the expected start date
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, and accomplishments in the field for candidates with recent PhD (within 1 year of application). Applications and supporting materials should arrive by 23 January 2026, for full consideration. However