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backgrounds in: Civil, Architectural, and Environmental Engineering, Computer and Software Engineering, Computer Science, or a related discipline such as Mechanical Engineering. Candidates must have completed a
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their use in model validation Knowledge of wind farm parameterizations in mesoscale models Experience with wind resource assessment and site suitability, including WAsP and WEng software Experience using
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Software Defined Vehicles (SDV). The primary objective is to expand, mature, and industrialize a novel European RISC-V automotive ecosystem that enables next-generation high-performance European automotive
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knowledge on principles of animal disease transmission and control Proficiency in statistical software (e.g., R, SAS, or similar). Creative and interested in exploring new technology and in adopting new ways
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postdoc focused on developing new cement formulations and characterization techniques. For algorithms and software there will also be the opportunity to work with the team behind the Core Imaging Library
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interest in pursuing applied research in computer vision and deep learning with a focus on wind energy application. Proven experience with computer vision tool/software development using Python and/or Matlab