47 parallel-computing-numerical-methods Fellowship 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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environments, and high-performance or parallel computing is desirable. The candidate will also prepare technical documentation, reports, peer-reviewed publications, and presentations and collaborate
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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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, dynamic-link libraries, SQL, Git or other version-control systems, Linux, high-performance computing, parallel computing, or automated testing Experience with watershed processes, groundwater-surface
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. Significant experience using Python for high performance applications with libraries such as: Numpy, Numba, CuPy, and PyQtGraph Significant experience using C++ for numerical computing applications
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Desired Qualifications Strong background in biomechanics, biomedical engineering, computational mechanics, or equivalent fields. Strong foundation in numerical methods, especially the finite element
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, data analysis, and visualization environments/IDEs (e.g., R/R Studio, Python/Spyder/VSCode) Familiarity with GIS methods and cloud-based computing resources (e.g., Google Earth Engine) for large-scale
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are expected to conduct research independently, apply and develop advanced computational methods, communicate findings internally at regular intervals, disseminate results externally through peer
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other institutions including the U.S. Department of Agriculture and several universities to improve upon existing remotely sensed data, develop new methods for detection of land management practices
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a variety of methodological backgrounds, which is reflected in the mixture of quantitative and qualitative research methods we are using for this project. One important goal of our research is to