46 component-labeling-cuda PhD positions at Technical University of Denmark in Denmark
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position to work at the intersection of transportation science, operations research, and transport economics. The PhD position is part of a strategic collaboration between the Technical University of Denmark
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activity in pathological and regenerative wound healing scenarios. The PhD project is part of the Marie Skłodowska-Curie Action Doctoral Network REMOD-HEALING, which aims to target extracellular matrix
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for Quantitative Sustainability Assessment of the Department of Environmental and Resource Engineering (DTU Sustain). The section spearheads the development of sustainability assessment methods. You will become part
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Denmark, NeoGrid, and Watts) on problems that matter today, as part of the EUDP-funded “Data Unlocked” project. Great environment: Join DTU Wind and Energy Systems, a world-leading research hub near
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the redistribution of the phases present, reaction mechanisms will be investigated and the information gained will be used for optimization of the battery. The position is part of the INCEPTION Doctoral Network
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will learn and adapt the realms of the combustion modes and fine tune the performance for each while the engine is operated. Self-tuning, adaptive, control algorithms will be used. This part of the three
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serve as co-supervisors. A secondment at Technical University of Munich, Straubing, Germany, is an essential component of the project and will contribute to the interdisciplinary nature of your PhD. You
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amongst the leading international entities in technology entrepreneurship and helps develop an entrepreneurial culture across DTU. As part of a dynamic and evolving ecosystem, we combine practice-oriented
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Ghaddar (DTU/Ivey/IE) and Professor Claudia D'Ambrosio (LIX Ecole Polytechnique/CNRS). You will be enrolled at DTU and you will be part of a vibrant international network with research visits at LIX Ecole
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funded PhD scholarships (3-year employment) in a vibrant interdisciplinary research environment. The positions are part of the research project “AI-driven materials optimization for light trapping in thin