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and process optimization to achieve safer and more efficient PFAS destruction. Your primary tasks will be to: Design and conduct laboratory-scale UV photochemical experiments Investigate
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fluorescently label CTCs, enabling precise isolation and downstream single-cell analysis. Using state-of-the-art Orbitrap mass spectrometry, automated sample preparation, and computational integration with
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: Microphone array processing. Acoustic measurements. Statistics and machine learning. Optimization and inverse problems. Excellent communication skills. Your primary responsibilities will be: Conduct original
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” funded by the VILLUM FONDEN. The overall aim of the project is to introduce microstructural engineering to the field of additive manufacturing (AM) of metals. This is to set the stage for optimizing metals
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, optimization, control, game theory, and machine learning. Interdisciplinary by design: Work at the intersection of energy systems and markets, privacy and cybersecurity, forecasting, optimization, control, game
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challenges. This PhD project aims to advance the efficient, controllable, and optimized use of renewable energy by integration of advanced TES technologies (latent heat and thermochemical storage) in
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batteries (RFB), enabling affordable and durable long-duration energy storage. The approach is to use hierarchical structures, i.e., complex material layers that can be optimized to specific battery
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, have been optimized for fossil fuels for more than 140 years but the new fuels have properties that can enable a more efficient operation. Advanced combustion processes like HCCI, SACI and PPC will be