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The postdoctoral associate will be embedded in a collaborative research environment that brings together expertise in functional genomics, regulatory genomics, machine learning, population genetics, and human
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focused on using spatial profiling and machine learning of human specimens in combination with functional experiments in animal models to understand cancer initiation, progression, and metastasis. We
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structure modeling in cancer immunotherapy design. Profile A — AI PhD in machine learning, computer science, computational science, or a related field. Strong experience with deep learning (e.g., PyTorch
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | about 2 months ago
substantial intellectual independence and opportunities to collaborate closely with machine learning scientists developing predictive models of cellular function. Machine learning experience is not required
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postdoctoral researchers Engage with the nuclear sector and form positive working relationship between and across external academic, industrial and policy stakeholders Actively contribute to the Dalton nuclear
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engineering. You will be responsible for: Plan, develop and conduct world-leading research Win external funding for research Supervise postgraduate and postdoctoral researchers Engage with the nuclear sector
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Group Leader and Professor AI in Biology - Dept of Computer Science and Dept. Electrical Engineering
or equivalent experience in machine learning or a related quantitative field (Computer Science, Artificial Intelligence, Statistics, Mathematics, Physics, Computational Biology/Chemistry). Candidates will be
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. Required qualifications include a PhD or equivalent degree with exceptional expertise in machine learning as well as postdoctoral qualifications and teaching experience equivalent to the requirements of a
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field. • Experience conducting medical imaging research. • Experience developing artificial intelligence and machine learning approaches for research. • Strong command of statistical methods and their
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 2 months ago
substantial intellectual independence and opportunities to collaborate closely with machine learning scientists developing predictive models of cellular function. Machine learning experience is not required