28 algorithm-development Postdoctoral positions at Harvard University in Ireland-University-Ranking-2024
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impact. Our team leverages data pipelines to quantify data centers’ electricity and water use, emissions, and air pollution exposure and health impacts. The overarching goal is to develop an interactive
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Group invites applications for a Postdoctoral Fellow position. The research will develop and utilize emerging machine learning tools to remove bottlenecks in many-body simulations. Responsibilities: 1
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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 scholarship, and accomplishments in the field. Create a Job Match for Similar Jobs About Harvard University Harvard University is devoted to excellence in teaching, learning, and research, and to developing
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. The postdoctoral researcher will contribute to ongoing JWST programs and collaborative projects, while being strongly encouraged to develop an independent research program. The postdoc is expected to lead and
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, such as leptin, have been deeply studied, the majority remain poorly characterized because existing tools are inadequate to study the entire secretome. For this project, we will use newly developed
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teaching, learning, and research, and to developing leaders in many disciplines who make a difference globally. The University, which is based in Cambridge and Boston, Massachusetts, has an enrollment
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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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that are covered include (as examples) postdoc salary, the salary of a technician directly supporting the postdoc’s project, professional development opportunities, and/or specialized research supplies needed
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—are intended to foster the early career development of researchers who have transitioned or are transitioning from training environments in the physical/mathematical/computational sciences or engineering into