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. This work will involve: i) contributing to design and run new Large Eddy Simulation experiments; ii) and analyzing the LES output to generate training data; iii) using Machine Learning techniques to learn
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technologies and their applications, including financial and policy implications within a large organizational setting Expert knowledge of financial modeling and data analytics Expert knowledge of financial
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skills. Ideal applicants will also have experience with some combination of: a) Machine learning e) code optimization and software delivery f) big data visualization g) cloud computing h) web application
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of phylogenomics to work with Professor Tiago Simões. The Simões lab is broadly interested in phylogenetic methods and applications, using morphological and genomic data for reconstructing evolutionary
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This graphic notice ( ) means that you are leaving the NIH website. This external link provides additional information that is consistent with the intended purpose of this site. NIH cannot attest
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efficacy of such efforts. Responsibilities will include activities such as working with large public datasets, designing and implementing relevant experiments writing manuscripts, presenting research, and
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in using common programming and scripting languages to analyze or otherwise use large meteorological datasets, including numerical model output, field campaign data, reanalysis, and both remote and in
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for mass spectrometry data, with artificial intelligence/machine learning (AI/ML) being a major focus. They will have an opportunity to develop new AI/ML approaches for anti-doping, with a focus on
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topics such as robot learning, human-robot interaction, Generative AI, computer vision, closed-loop control, extended reality (XR), and computational design. Job Description We seek to hire outstanding
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apply online at https://puwebp.princeton.edu/AcadHire/position/39061 and submit a cover letter, curriculum vitae, a brief statement of research interest, and names and contact information for three