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. The overall aim of this project is to address these challenges by: Developing new data-driven and physics-based models of battery behaviour. Designing advanced BMS algorithms for real-time monitoring and
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developing a novel imaging and amperometry-based platform for research into neurological diseases. About us The Esbjörner lab belongs to the Division of Chemical Biology , which is part of the Department
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-fidelity qubits operations Design and implementantion of automatic calibration techniques for fast tune-up Implementation and benchmarking of quantum algorithms About you You have a relevant PhD deegree
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passive and active flow control algorithms, potentially incorporating machine learning/AI, to enhance aerodynamic performance and stall delay with rapid response times. The research is conducted in
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within research and education. The following will strengthen your application: Familiarity with any of: molecular simulation methods (integrators, force fields, enhanced sampling), structural biology