13 machine-learning-"https:"-"https:"-"https:"-"https:" research jobs at Michigan State University
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, numerical method, and data-driven/machine-learning approaches, including: · Numerical simulation of kinetic equations: fast algorithms with stability/convergence analysis; · Data-driven and machine
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-preserving, machine-learning–accelerated scientific computing for plasma physics applications. In particular, the project involves developing data-driven collisional kinetic models and numerical schemes
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Type IIP supernovae. We use data from current (ZTF, HST, JWST) and next-generation telescopes/surveys (LSST, WFIRST) to address scientific questions using machine learning and statistical methodology
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> on research projects related to kinetic equation and its related multiscale model reduction, numerical method, and data-driven/machine-learning approaches, including: • Numerical simulation of kinetic
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. Bioinformatics analysis of data will include use of population genomics techniques, phylogenetics and machine-learning development. The successful candidate will be expected to write up results as manuscripts
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discovery Bioinformatics/protein engineering/single-cell RNA sequence analysis Machine learning/deep learning Computational topology/geometry/graph. Research Associates will be affiliated with Professor
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especially looking for candidates with a background in Monte Carlo Event Generators, parton showers, neutrino-nucleus interactions, and machine learning applications in particle physics. The high energy
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Computer programming skills Desired Qualifications Experience developing computational tools for biomolecular systems Experience training machine learning models Experience working in a collaborative
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Experience with multivariate ecological statistics or machine learning and GWA Experience with Field research in agronomy or environmental microbiology Experience with gnotobiotic or controlled
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Experience with multivariate ecological statistics or machine learning and GWA Experience with Field research in agronomy or environmental microbiology Experience with gnotobiotic or controlled