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and machine learning based software to assist clinical workflow and pre-clinical studies. Recent software developed from the group has been adopted in the clinic and preclinic labs. The scientific
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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for energy yield prediction. - Develop models for performance loss rate analysis. - Conduct time series analysis and apply machine learning techniques to assess PV and energy storage system performance
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interdisciplinary team at the NSF COMPASS Center, which integrates tissue engineering, stem cells, materials, virology, computational biology, machine learning, molecular environmental engineering, science
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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&M AgriLife is uniquely positioned to improve lives, environments and the Texas economy through education, research, extension and service. Click here to learn more about how you can be a part of
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-performance computing. Additional experience in DNA biophysics, machine learning, and optimization is preferred. This job description intends to provide a representative and level of the types of duties and
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. GLW faculty draw on the fields of anthropology, economics, history, law, labor relations, political science, and sociology in their research and teaching. To learn more about the faculty in
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modeling. Brief Description of Duties: The Postdoctoral Associate will assist the Principal Investigator Dr Fang Luo in the Department of Electrical and Computer Engineering . The incumbent will conduct
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expected to develop and lead projects. Ideal candidates will have knowledge of population genomics, machine learning, and evolutionary theory. Candidates should have a strong track record of publication; be