597 engineering-computation-"https:" "https:" "https:" Postdoctoral positions in United States
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(NLR), where world-class scientists, engineers, and experts are accelerating energy innovation through breakthrough research and systems integration. From our mission to our collaborative culture, NLR
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Systems Department, in the School of Computer Science is looking to hire a Post-Doctoral Fellow in Policy for the Center for Informed Democracy and Social-cybersecurity (IDeaS) at Carnegie Mellon University
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Minimum Qualifications: Requires a minimum of a Ph.D. or (ABD) in engineering, hydrology, computational sciences, systems modeling, applied mathematics, or a related field. Preferred Qualifications
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and research staff. For a full list of department members and activities, see https://web.astro.princeton.edu/. There are also strong research groups with interests in astrophysics at the Princeton
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. You keep current of recent scientific, engineering and technical advances and are able to translate these into your research. The ideal candidate will have the ability to work both independently and in
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, mathematics, computer science, engineering or a related discipline Required Other None Additional Preferred Experience working in one of the following areas: Machine learning/predictive modeling
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engineering, computer science, applied mathematics, systems biology, or a related field. Strong background in computational modeling, data science, or machine learning. Candidates in ABD (all but degree) status
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Description Primary Duties & Responsibilities: Information on being a postdoc at WashU in St. Louis can be found at https://postdoc.wustl.edu/prospective-postdocs-2/ . Trains under the supervision of a faculty
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in the engineering sciences, applied mathematics, physics and computational sciences will be considered. Individuals comfortable with machine learning, the JAX library, finite element methods, and/or
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in the engineering sciences, applied mathematics, physics and computational sciences will be considered. Individuals comfortable with machine learning, the JAX library, finite element methods, and/or