78 computer-science-intern-"https:" "https:" "https:" "https:" research jobs at University of Minnesota in United States
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theoretical and computational solid mechanics, fluid dynamics, hypersonics, aerospace systems, and aerospace structures and materials. The department is in the College of Science and Engineering at
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% of eligible tuition Student loan forgiveness opportunity Opportunities for growth and promotion Employee Assistance Program For more information regarding benefits: https://humanresources.umn.edu/sites
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transportable. A graduate student with a physics background is needed to perform software-assisted design of system components, write and apply computer programs capable of simulating MRI pulse sequences, and to
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for autonomous vehicle control and teleoperation applications. Expertise in the areas of vehicle dynamics, vehicle control, localization, computer vision, sensor fusion and estimation algorithms is desired
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Qualifications: PhD in computational genomics Experience with: • Computational and bioinformatics • Machine learning and statistical modeling • Programming and data infrastructure • Experimental and Field Methods
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Previous Job Job Title Researcher 3 - Cancer Biology Next Job Apply for Job Job ID 373331 Location Twin Cities Job Family Research Full/Part Time Full-Time Regular/Temporary Temporary Job Code
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, epidemiology, veterinary population medicine, quantitative biology, environmental science, or a related field Demonstrated experience developing statistical or machine-learning models using R or similar
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results, and discussions of possible new approaches with team members and the Principal Investigator. Qualifications Required Qualifications: PhD in Statistics, Biostatistics, Computer Science, Electrical
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%) Code in Matlab or other program for stimulus generation, presentation, and analysis, as well as data analysis. (25%) Prepare data for publication and presentation via peer-reviewed journal articles and
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additionally include grant/fellowship applications, and presentation at conferences • Read and internalize relevant literature to ensure well designed, executed, analyzed, and interpreted experiments • Properly