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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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). Practical experience with cloud computing platforms (e.g., AWS, GCP, Azure). Additional Qualifications Experience with multi-GPU model training and large-scale inference. Familiarity with modern AI
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and neural activity. In particular, Postdoctoral AI Researchers may help develop brain foundation models that predict patterns of neural activity from large-scale, multi-regional recordings. Areas
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, interdisciplinary environment. Additional Qualifications Prior experience with one or more of: ● Health claims data, EHRs, or other large-scale health/administrative datasets. ● Environmental, climate, or air
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. Familiarity with models and methods relevant to protein and cellular biology, including AlphaFold, RFDiffusion, CellCap, or related systems. Experience with large-scale datasets, distributed training, or high
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statistics, computing, machine learning (ML), and genetics and genomics, with a focus on large-scale genetic, genomic, and phenotype data. The work will involve both methodological research and collaboration
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for candidates with interests in multiscale simulations of complex physical phenomena, from the atomistic/electronic scale to mesocopics and beyond. Of particular interest is the development and application
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, tool use, retrieval systems, or related AI systems Experience with large-scale datasets, distributed training, or high-performance computing environments Interest in scientific applications of AI/ML
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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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biology and genomics. We are collaborative and multidisciplinary, combining organic chemistry, cell and molecular biology, protein biochemistry, and large-scale genetic screening in our research approach