21 machine-learning-"https:" "https:" Postdoctoral positions at University of Washington
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candidates with strong expertise in Bayesian methods, uncertainty quantification, and/or machine learning applied to nuclear theory. The group’s research spans a wide range of topics including nuclear
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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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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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, 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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a novel multi-omics approach that integrates high-throughput imaging and machine learning methods with CRISPR/Cas9 screens and saturation mutagenesis to answer central questions about the
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excellent at training new users of HCP-Style brain imaging methods. Job Description Primary Duties & Responsibilities: Information on being a postdoc at WashU in St. Louis can be found at https
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the Center’s co-founders and affiliate faculty, including sociologists, information scientists, computer scientists, and policy experts. Located in Seattle, the position also offers opportunities for engagement
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computer vision and machine learning approaches to integrate ground-based imagery, remote sensing data, and lidar data for high-resolution flood detection and mapping. Develop and calibrate hydraulic flood
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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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. The postdoctoral researcher will take a lead role in designing and conducting experiments to assess how people with spinal cord injury learn to control their legs in a novel body-machine interface using wearable