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National Energy Technology Laboratory (NETL) | Morgantown, West Virginia | United States | about 1 month ago
Engineering, Systems Engineering, Data Science, or a closely related field Experience with artificial intelligence, machine learning, physics-informed neural networks, or reduced-order modeling (ROM
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to, atmospheric science, environmental engineering, earth observation, and computer science. Strong programming skills and experience with machine learning applications in geoscience are highly desirable
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Sciences, Geodesy, Physics, Mathematics, Computer Sciences, Civil & Environmental Engineering, or a related field. PhD awarded no more than four years prior to the effective date of appointment with a
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. The postdoctoral scholar will contribute to an exciting research program within the Foy Lab (www.foylab.xyz/) https://foylab.xyz/ , developing machine learning, computational, and mathematical models for improving
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to, atmospheric science, environmental engineering, earth observation, and computer science. Strong programming skills and experience with machine learning applications in geoscience are highly desirable
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approaches such as non-coding CRISPR screens, the Massively Parallel Reporter Assay (MPRA), saturation mutagenesis, and synthetic sequence design, alongside machine-learning models of regulatory grammar
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 2 months ago
, computer engineering, or a related discipline. Strong motivation, scientific curiosity, and commitment to scientific excellence. Experience in one or more of the following areas: electronics and
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, biomedical engineering, medical technology, optics, mechatronics, computer engineering, or a related discipline. Strong motivation, scientific curiosity, and commitment to scientific excellence. Experience in
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will engage in research that includes applied machine learning, systems building, and Internet measurements. Key Responsibilities: Contribute to driving and developing the lab's research directions and
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systems. • Develop and implement predictive models for packaging performance using machine learning approaches and physics-based simulations. • Investigate logistics optimization strategies for packaging