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areas: Generative AI Agentic AI Graph Representation Learning and Modeling Foundation Models Large Language Models Multimodal Learning Forecasting Models Basic Qualifications A Ph.D. or equivalent degree
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individuals with expertise in one or more of the following areas: Generative AI Agentic AI Graph Representation Learning and Modeling Foundation Models Large Language Models Multimodal Learning Forecasting
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will lead and participate in observations and data analysis across the electromagnetic spectrum, or will lead work on machine learning classification of optical transients. Applicants with previous
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information, and/ or data analysis are strongly encouraged to apply, as these skills will be preferred in the selection process. This appointment duration is up to three years, with reappointment contingent
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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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gain experience in pooled screening techniques including library cloning, CRISPR screening, protein purification, proteomics and sequencing. We will use Python and Bash scripting to analyze and visualize
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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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for analysis of large-scale whole genome genetic and genomic and phenotype data. Examples include large Whole Genome Sequencing association studies, biobanks, single-cell and CRISPR multiome data, integrative
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will work with Prof. Daniel Eisenstein and collaborators on the analysis and interpretation of JWST data, with particular emphasis on deep-field observations. The position provides access to large, high
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domain-specific foundation models that support tasks such as forecasting, interpolation/extrapolation, downscaling, and “what-if” scenario analysis relevant to climate-related health risks and adaptation