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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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to work) in reduced order modeling, Causal inference and High Performance Computing are desirable. We particularly encourage applicants with expertise in Multi-scale Modeling, Evolutionary Computation
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to open-source code, reproducible research workflows, and, where possible, public tools or model artifacts. Basic Qualifications ● PhD (completed or near completion) in one of the following or a closely
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, spatiotemporal modeling, high-dimensional statistics. ● Proficiency in statistical programming (R and/or Python) and good practices for reproducible research. ● Experience working with large datasets and cloud