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python), computational mechanics and fluid dynamics, numerical methods, machine learning, and the finite element method. In this position, the candidate will develop data-driven multiscale/multiphysics
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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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conduct collaborative research at the intersection of non-canonical kinetic theory, non-conventional plasma turbulence modeling, high-speed flows, scientific machine learning for multi-physics problems
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trials to multi-omics explorations, imaging, biomarker development, stable-isotope tracers, and large-scale data set s and machine learning. The lab is now recruiting for a postdoctoral researcher, who
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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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Element Method modeling (Abaqus, Ansys) or similar. 4. Basic familiarity with machine learning (preferred). 5. Some record of research output (e.g. peer-reviewed papers, conference abstracts) or
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physiology, time-series analysis, machine learning and deep learning, multi-modal data integration, systems biology and/or mathematical and mechanistic modeling are beneficial. An ideal candidate will
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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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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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modeling, medical image processing, and machine learning techniques. Excellent communication and written skills. Required Application Materials CV and cover letter Website me.msu.edu MSU Statement Michigan