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). This project aims to accelerate the energy transition in Luxembourg by co-creating an ambitious research program. It will utilize a data-driven approach to support decision-making for an optimal energy system
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assist the research progress of doctoral students towards graduation without delays, thus ensuring an optimal graduation time of four years for PhD candidates. Because of the close ties with the research
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that can self-learn bulk visco-elastic properties? How to structure such materials to learn continually and counteract the aging of their own parts? Can we optimize self-learning materials to achieve
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will employ a data-driven approach and state-of-art methodologies to support decision-making for an optimal and smooth integration of the e-mobility sector, with specific focus on cost-effectiveness
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through optimization of ion channels incorporation and activity in lipid bilayers. The project sits at the interface of biophysics, engineering and biochemistry. The PhD student will be part of
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at the University of Stuttgart. It is an international doctoral programme in the field of Environment Water (ENWAT) and hosts, at present, roughly 50 doctoral candidates. At the moment, five different institutions
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topologies tailored for DC-powered HVAC units Synthesis and implementation of control strategies enabling droop-based HVAC operation with optimized energy efficiency Implementation of simulation models (PLECS
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Job Description Are you interested in putting science in direct benefit of society? We are offering a full PhD fellowship to explore how AI, Mathematical Optimization, and Game Theory can be used
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an optimized extraction process for bioactive compounds from seaweed. Analyse and characterize the extracted compounds for their bioactivity and techno-functional properties. Support student supervision and
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, or conditional deletion of defined dendritic cell subsets, providing powerful genetic tools for dissecting cell-specific roles in vivo. Using and optimizing these tools to study Type 3 Dendritic cells in mouse