108 assistant-professor-and-human-computing Postdoctoral positions at University of Washington
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conditions, and brain tissue microstructure and functioning. The successful candidate will be working within a multi-disciplinary team of MRI physicists, computer scientists, radiologists, neuroscientists, and
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mentor including (but not limited to): Human Subjects Research Design and conduct research experiments following instructions and discussions with principal investigator. Develop procedures for data
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the supervision of a faculty mentor including (but not limited to): Human Subjects Research Design and conduct research experiments following instructions and discussions with principal investigator. Develop
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Science 371:1154). The position will involve utilizing human specimens, cell culture models (epithelial and immune cells) and testing hypothesis in mouse models of the disease. Appropriate training in all
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statement of research interests, and contact information for three referees. For questions please email: Dan Zhu, PhD, Research Assistant Professor of Radiology, Assistant Director of MRI Protocols for DISC
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associated clinical outcomes. The fellow will be responsible for identifying computational approaches for data selection, processing, and predictions/inference. The expected outcome of the project is to
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of the Planetary/Environmental Health IRN is to understand how changes to the environment affect human health, and find sustainable ways for people to live healthier lives while maintaining the health of the planet
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multidisciplinary institute with a core mission to advance civic health through interdisciplinary research and education initiatives that help individuals, communities, and institutions navigate our complex
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infertility and miscarriage. The candidate will carry out the research work under the supervision of Assistant Professor Min Yang within the Center for Reproductive Sciences at the Department of Obstetrics and
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about exploring and applying new statistical, computational, or machine learning techniques to astronomical data sets, and extending current methodology to be applicable in the era of big data. Looking