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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 19 hours ago
as well as for federally funded social and behavioral sciences research and development. Here at Carolina, our highly skilled postdocs play a vital role in our research enterprise and towards our
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wider society. Chalmers was founded in 1829 and has the same motto today as it did then: Avancez – forward. URL to this page https://www.chalmers.se/en/about-chalmers/work-with-us/vacancies/?rmpage=job
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Job Id: 11788 Limited to 3 years | Full-time with 38.5 hours/week | Salary according to TV-L E13 | Clinical Epidemiology Unit at the Institute for Epidemiology and Social Medicine We are UKM. We
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management; the incorporation of fault detection and diagnostics (FDD) into industrial energy systems; building energy performance simulation; and the application of next-generation renewable and sustainable
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position is associated with the Robot Navigation and Perception Lab (https://rnp.aass.oru.se ) which belongs to the Centre for Applied Autonomous Sensor Systems (AASS) research environment (https
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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description This one-year postdoctoral project aims to use multi scale atomic simulation
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performing atomistic simulations with Density Functional Theory and Molecular Dynamics. Data analysis and coarse graining in order to provide parametrisations for upper scale models (Kinetic Monte Carlo and
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the range of optimal physical parameters associated with flow/viscosity pairs of the algal solution in order to achieve good uniformity of residence times. The BioACE project aims to develop a new type of
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partner from data sciences provides data management and AI based Image analysis, an internal simulations group working on quantitative models to reproduce and predict experimental data, and an internal