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, learning on the job, and collaborating with other researchers in an informal collegial work environment imbued with intellectual rigor. They should possess an outstanding academic record and strong
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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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applications to teach in the Sophomore Tutorial program. Tutor positions are open to advanced graduate student and postdocs/PhD-level early career instructors with prior teaching experience. Sophomore Tutorial
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an individual with a PhD to conduct research in the area of biomedical informatics, multi-omic integratoin analytics and machine learning. In this role you will produce highly impactful biomedical informatics