11 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" Postdoctoral positions at University of Washington
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The Department of Biostatistics at the University of Washington has an outstanding opportunity for a postdoctoral scholar. The postdoctoral scholar will develop statistical machine learning and artificial
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or more projects, learning advanced cellular and molecular biology and anaerobic microbiology techniques. The candidate’s day will be split between benchwork to generate data, and computer work to generate
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morphology (e.g., geometric morphometrics, machine learning), and phylogenetic comparative approaches. We have: • An engaging, supportive, and collaborative research environment. • Opportunities
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with other scientists and the public in an accessible manner The salary for this position will be $6200-$7000 per month, commensurate with experience and qualifications, or as mandated by a U.S
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computer simulations, as well as prior work with food and other biomaterials. The application deadline is December 15, 2025. Interested applicants are encouraged to contact Juming Tang (jutang88@uw.edu
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include experience with fiber sensing, machine learning tools, and big data workflows. Instructions To apply, candidates will submit materials via Interfolio, comprising (1) a letter of interest describing
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, atmospheric signals), data fusion across sensing modalities, and development of scalable machine learning pipelines. Work will be entirely computational and based in Seattle, with no field deployment
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based on predictions from statistical and machine learning models Postdoctoral scholars are represented by UAW 4121 and are subject to the collective bargaining agreement, unless agreed exclusion criteria
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undergraduate students. Ability to manage priorities and timelines. Applicants must be U.S. citizens or permanent residents at the time of application. Desired Qualifications: Expertise in the design and testing
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focus in machine learning. The postdoctoral scholar will work on topics of mutual interest such as, but not limited to, automatic machine learning model selection and automatically explaining machine