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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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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
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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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include the design and implementation of finite element multiscale models and machine learning algorithms, analyzing related experimental data, and collaborating with industrial collaborators to validate
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these questions, we will determine RNA structures in vivo using cutting-edge transcriptome-wide RNA structure probing techniques that together with computational models and machine learning algorithms will generate
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Scientific Computing the research and education has a unique breadth, with large activities in classical scientific computing areas such as mathematical modeling, development and analysis of algorithms
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of automotive datasets. The research tasks in this project are linked to this objective and consist of reviewing related literature and conducting experiments with dataset(s) and approaches/algorithms in the area
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synchrotron radiation methods. Experience in programming, data analysis, and algorithm development. (MATLAB, Python, C++, etc.) Experience in developing simulations related to X-ray characterization Track
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the opportunity to develop your own research ideas within the lab’s focus areas Build and refine computational models of human innovation and learning processes Design and test AI algorithms