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, including the Volvo Car Technology Award, placement on IVA’s 100 List, and best paper awards from IEEE VTS and PELS. We have published over 50 high-impact journal papers and hold several patents. Our
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system complexity. Your work will include: Developing modular, efficient, and transparent control algorithms. Combining model predictive control with learning-based motion prediction under uncertainty
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modeling, and algorithm development, with experimental validation using Chalmers' advanced multi-antenna testbed. The overall objective is to contribute to the development of energy-efficient and high
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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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before the application deadline* Demonstrate strong mathematical skills, particularly in optimization and algorithm development Have a publication record in peer-reviewed journals (e.g., IEEE Transactions
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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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driving range. The project aims to analyze algorithms for predicting the remaining driving range of EVs and suggest ways to improve the current state of the art. The idea is to develop a model-based