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, including, but not restricted to, geometry or shape optimization, parameter optimization, or multi-objective optimization. · Strong programming skills (e.g. Python, C/C++, R or similar) and experience
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | 3 months ago
for the position of research assistant professor with a significant outreach component. Expectations of the position will be to develop an externally supported research program in agroforestry and contribute
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better than 2.5 - Very good programming skills (e.g., Python, JavaScript/Angular/Electron, C++, or comparable) - Experience in the development of simulation environments or experimental software platforms
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through the tuition remission and dependent education programs. See the Benefits home page for more information. Position Summary The University of New Mexico, Health Sciences Center, Department of
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Description KIT Graduate School Computational and Data Science (KCDS) is a graduate school at KIT Center MathSEE that offers an interdisciplinary training program for doctoral researchers in
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with our industrial and UK university partners, a novel research programme will be implemented based on modelling, control and optimisation of an integrated power and transportation networks. Key
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is a Workplace Substance Abuse (WSAP) testing designated position. WSAP positions require passing a pre-placement drug test and participation in an ongoing random drug testing program. In addition
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of Research (2 pages): What research do you plan to pursue during the fellowship term? What do you plan to do at each stage, and what particular resources do you intend to use? What are the advantages
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”. A precondition for application would be a Master degree in economics (or alternatively, an current enrolment in a doctoral student program in economics). We expect previous activities in economic
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research program that brings together physics, chemistry, and machine learning. Your research tasks will include: Uncertainty Estimation in Deep Neural Networks for MLFFs Implement and test uncertainty-aware