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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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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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Models Basic Qualifications: A Ph.D. or equivalent degree in Machine Learning, Computer Science, Electrical Engineering, Geophysics, Applied Mathematics, or a closely related field. Demonstrated strong
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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 related field: Computer
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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 ambitious research at the intersection of machine learning, neuroscience, and computational biology. This role centers on computational neurobiology and the use of modern AI/ML methods to model brain circuits
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computational biology or biological data analysis. Strong candidates may come from protein-focused, cell-state-focused, or multimodal biological modeling backgrounds and will have expertise in one or more of the
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Details Title Postdoctoral AI Researcher in AI/ML for Foundation Models, Scientific Applications, and AI Systems School Faculty of Arts and Sciences Department/Area Kempner Institute at Harvard
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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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version control ● Experience working with large datasets and cloud computing environments. ● Solid background in statistical modeling and inference ● Excellent written and oral communication skills, with a