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, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to apply
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. transformer models). One focus of this work will be on B-cell receptor evolution. Experience in applications of modern machine learning methods as well as in biological data analysis are needed for the position
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preferential viewing behavior, using large-scale electrophysiology, behavioral experiments, and computational modeling. We welcome applications from recent PhD graduates who are interested in these or related
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changes in sensory coding. We welcome applications from recent PhD graduates who are interested in these or related fields, particularly those who may bring a new technology or perspective to bear on
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studies how cancer and healthy cells respond to irradiation and DNA‑damaging drugs, using quantitative live‑cell imaging at the single‑cell level. We welcome applications from recent PhD graduates
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have a PhD in physics, biology, or a related field by the time of appointment. The ideal candidate will also have demonstrated experience in machine learning and biological data analysis and a strong
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focusing on multi-omic integration analytics, machine learning, and/or AI. In addition to carrying out research, the successful candidate will be expected to apply for fellowship funding, contribute
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on projects at the intersection of computational neuroscience and machine learning. This position is part of a multi-investigator grant on the role of memory in intelligence systems. The Postdoctoral Fellow
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an environment that is diverse, inclusive and respectful. Learn more about our lab here: https://bioniclab.seas.harvard.edu/ We are recruiting fellows from diverse backgrounds interested in solving tough problems
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quantum chemistry, experience with machine learning regression methods. Preferred start date as soon as possible but flexible. Basic Qualifications PhD in Physics, Chemistry, Materials Science, Computer