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models. However, rigorous methods for evaluating XAI algorithms are currently lacking. This is in large part due to a gap between how explainability is evaluated within computer science and philosophy. In
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of two years. About the Project The successful candidate will advance the algorithmic and theoretical foundations of reinforcement learning applied to complex, high-dimensional dynamical systems
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. The tasks include battery cell characterization and modelling based on laboratory tests, and development of algorithms for estimating the charge level, health, and power capability which includes robustness
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data, variant discovery and filtering, and downstream population-genetic and evolutionary-genomic analyses. The work will require substantial data processing, quality control and computational
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collaboration while providing access to cutting-edge facilities. About the research project The focus of this project is the epidemiology and shared genetics of eating disorders and personality (EpiGen-EP
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languages. The section is part of the Department of Mathematics and Computer Science, and other research sections at the department are Algorithms Computational Science Data Science and Statistics Geometry
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sensing technologies (camera, Electromagnetic tracking system, FBG sensing) with continuum robotic systems and development of associated sensing and estimation algorithms 3D environment reconstruction based
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analytical skills. Knowledge about statistical machine learning, robotic perception, multimodal AI algorithms. Proven experience with reinforcement learning algorithms and implementations. Experience in
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of these experiments. As part of this, we have developed new algorithms and a completely new web-based platform – EasyNMR - for performing such modelling/simulations. With this position, we seek to strengthen
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characterization of milk-derived extracellular vesicles” to join us at the Department of Molecular Biology and Genetics in the research team of Jan Trige Rasmussen. Expected start date and duration of employment