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recordings. Experience with large-scale datasets, distributed training, or high-performance computing environments. Experience with foundation model training, post-training, adaptation, or evaluation
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Qualifications Experience with foundation model training, post-training, adaptation, or evaluation. Experience with protein structure modeling, protein–protein docking, or small-molecule–protein docking
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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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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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of the primary objectives of the ITC is to integrate conceptual theory with computational modeling. We are, therefore, interested in candidates working in any field related to theoretical and/or numerical
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, digital health, and policy issues under the mentorship of Prof. Haiden Huskamp, and the provision of primary care services, with a focus on the patient-level impacts of primary care physician work effort
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, digital health, and policy issues under the mentorship of Prof. Haiden Huskamp, and the provision of primary care services, with a focus on the patient-level impacts of primary care physician work effort
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of the following areas: surface characterization using spectroscopy and electron microscopy; macroscale electrochemistry; Finite Element Modeling with COMSOL Multiphysics; and an appreciation
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Science, Computer Science, Applied Mathematics, Engineering and Physics. Additional Qualifications Expertise (or desire to work) in reduced order modeling, Causal inference and High Performance Computing
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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