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machine structures, together with AI-driven optimization frameworks for diverse applications while considering LCA metrics. The success of this project could serve as a model for other energy-related
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and other stakeholders to gauge and optimize the ecological and bioeconomic consequences of North Sea OWF expansion. The announced PhD position focuses on foraging and life-cycle ecology of fish and
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multidisciplinary research in energy markets, optimization, game theory, and machine learning. Our team of 13 members (link ), from 10 different nationalities, values diversity and includes experts from a range of
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electromagnetic simulation techniques and incorporate the characteristics of new materials to design motor structures, and perform multi-objective optimization aimed at enhancing motor efficiency, power density
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) project, we are looking for a motivated and experienced PhD candidate to perform consumer flexibility aware planning of multi-energy districts. A particular focus lies on the modelling and optimization
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criteria Demonstrated knowledge and experience in electrical system modeling and analysis, applied control, power electronic systems, optimization techniques, and/or machine learning. Experience with
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and embrittlement by precisely optimizing additive manufacturing parameters. By combining experimental investigations, advanced microstructural analyses, and numerical simulations, a novel manufacturing
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thermochemical TES. Your main supervisor will be Prof Adriano Sciacovelli and you will join the Thermal Energy Section at DTU Construct. Your work will contribute to a paradigm shift in how complex TES systems
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reactors, can be optimized for N2O mitigation or ultimately complete N2O removal. Overall, the project represents a unique opportunity to engage with the water utility sector with regards to greenhouse gas
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Your Job: You will join the "Electrocatalytic Interface Engineering" department, led by Prof. Dr.-Ing. Simon Thiele, and the "Membrane Polymer Synthesis" (MPS) team by Dr. Jochen Kerres