68 parallel-computing-numerical-methods-"https:" Postdoctoral positions at University of Minnesota
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computational mechanics, FEM/Particle methods, time integration and analysis (60%); -help to write quality research proposals to government agencies and industry, prepare/assist in journal research papers/book
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development, data management, and preparation of scientific reports (20%) Computer knowledge to enter data from experiments into existing databases; spreadsheets and web-based applications. Conduct background
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sponsorship. *Duties/responsibilities: -performing high level experimental, theoretical, and numerical research and data analysis (55%) -presentation publication, and proposal preparation (20%) -mentoring PhD
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sponsorship. *Duties/responsibilities -performing high level experimental, theoretical, and numerical research and data analysis (55%) -presentation publication, and proposal preparation (20%) -mentoring PhD
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team of undergraduate/postgraduate researchers. Candidates should be able to multitask parallel evolution experiments with phenotypic and genomic analyses. Job Duties and Responsibilities: Typical tasks
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of Minnesota, working with Professor Russell Funk. This position focuses on using computational methods to understand how knowledge is produced, shared, and applied across complex systems. About the Project
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-doctoral Associate will develop algorithms and theory for machine learning methods, as well as implement and apply ML methods to problems in domains such as computational biology and neuroscience. This is a
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-disciplinary research team, consisting of researchers in coil development, electromagnetic simulation, parallel transmit RF pulse design, pulse sequence development, advanced MR image processing, analysis and
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leverages the novel single-asperity nanoscratch method and other advanced AFM modes to visualize the mechanism of nanoplastic release and to identify unique nanoscale properties that result in health impacts
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group focuses on mixed-methods studies on attitudes related to SOGI and bias-based bullying in schools. The successful applicant will work collaboratively with colleagues, engage in the recruitment and