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Job Description Do you want to contribute to a new research field where oxide/metal hybrid devices are geometrically optimized to yield extraordinary performance, including the highest
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for industrial decarbonization with emphasis in system development, modelling, optimization and validation, and focus on: Develop thermally integrated storage and conversion systems, including Carnot batteries and
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our team at DTU Compute, offering a fully funded position within a dynamic and interdisciplinary research environment. The positions are part of the research project “AI-driven materials optimization
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of energy and a large part of this energy is used for conditioning indoor environments. There is a global need to identify heating, cooling and ventilation (HVAC) solutions that create optimal indoor
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collection. Evaluate protein content, nutritional value, and functional properties of yeast biomass in various fermentation processes. Develop and optimize both liquid fermentation strategies offering high
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partners and optimize them for nonlinear quantum processes Collaborate with theory colleagues to refine fiber designs based on experimental feedback Disseminate results at international conferences and in
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to relevant external sources. By enabling data interoperability across facilities and process units, this infrastructure will allow real-time coordination, intelligent scheduling, resource sharing, and improved
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, or reinforcement learning Proficiency in Python and contemporary software ecosystem for optimization, dada management, and API development Experience with teaching and supervision Experience with IoT, edge computing
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. Responsibilities: Conduct research in compilation, optimization, and analysis for time-predictable computer architecture. Co-supervise MSc and PhD students. Contribute to teaching and research proposal preparation