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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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or similar. Background in applied physics/materials science. Experience in STM Experience in programming or writing analysis software is advantageous. Previous experience in nano/micrometer-size device
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at DTU Compute. The position is part of the large EU project Shift2SDV, which brings together 81 partners to shape the future of Software Defined Vehicles (SDVs). DTU’s role is focused, and the postdoc
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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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developed python-based EM forward operator. Contributing to the development of a freeware software package that offers both forward and inverse modeling capabilities for FEM and TEM data. Collection of FEM
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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
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Bioinformatics with at least one first-author publication, accepted or submitted Experience with machine learning will be a plus (e.g., Tensorflow/Keras/PyTorch). Experience with software containers and/or