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merit and even better is knowledge of adaptive control, machine learning and AI. But the most important qualification is an eagerness to learn the mysteries of fuel-combustion-engine interaction. You must
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batteries (RFB), enabling affordable and durable long-duration energy storage. The approach is to use hierarchical structures, i.e., complex material layers that can be optimized to specific battery
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within the broad topics of modelling tool-workpiece interaction in mechanical material removal processes, zero-defect manufacturing, machining system performance characterization as well as on-machine and
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life-cycle dynamics, evolving local contexts, and structural societal changes. The network includes five European universities and several non-academic partners, offering interdisciplinary supervision
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where variable renewable energy sources are involved. Emerging digital and cyber-physical systems technologies are an integral component of grid interactive efficient buildings. Through advanced control
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materials built by covalent linking of monomers, supramolecular polymers are dynamic and formed by the self-assembly of monomeric units brought together by non-covalent interactions. The connections between
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tools such as RFdiffusion2 or BoltzDesign. Perform molecular dynamics simulations and in silico screening to assess inhibitor-target interactions and predict selectivity. Clone, express, and purify top
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batteries (RFB), enabling affordable and durable long-duration energy storage. The approach is to use hierarchical structures, i.e., complex material layers that can be optimized to specific battery
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Programming skills in Python, R, and/or GIS tools Highly valued: Background in LiDAR point-cloud analysis and vegetation structure analysis or habitat monitoring Experience applying AI or machine learning
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Programming skills in Python, R, and/or GIS tools Highly valued: Background in LiDAR point-cloud analysis and vegetation structure analysis or habitat monitoring Experience applying AI or machine learning