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Position in Synthetic Biology and Metabolic Engineering (m/w/d) to be filled as soon as possible. The position is initially limited to three years. The research group headed by Prof. Dr. Hannes Link
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Your Job: Your research will explore the integration of emerging energy technologies into future energy systems and assess their potential contributions toward a greenhouse gas-neutral Europe. A key
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systems on different temporal and spatial scales. For our Research Group Applied Optimization we are looking for a Research Associate / PhD: Physics-informed deep learning for PDE-constrained optimization
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electrolyte and electrodes and their influence on the overall performance and safety of sodium-based batteries and their chemistry You cooperate with partners from theory to optimize charge transport
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assessment, you will develop new, sample-efficient optimal control approaches for gate calibration and test them in numerical simulations. You will pursue your research with the German research collaboration
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systems on different temporal and spatial scales. For our Research Group Applied Optimization we are looking for a PhD student: New Deep Learning - based Framework for Energy Modelling: Combination
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, operation and optimization of fs to ps laser sources Characterization of electrostatic potentials and excited carrier concentrations using off-axis electron holography Mapping of charge carrier lifetimes by
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, miniaturised devices for biomedical research, and to other specialised applications. However, our current understanding of the key factors that affect their performance is limited by the fact that most
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addition to technical models allowing to assess technical scaling and an optimal operation. The optimal plant design is identified by considering the energy supply system, the choice of capture technology, the DAC
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the Research Group “Nonlinear Optimization and Inverse Problems” (Head: Prof. Dr. D. Hömberg) starting as soon as possible. The project is part of a BMBF project concerning industrial scale data preparation