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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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pharmaceutical sciences, in which data science is applied to drug discovery, development, and safety, algorithms and databases are developed and tailored to pharmaceutical data, and data drives pharmaceutical
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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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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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and experiments with modelling 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
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establish new strategies to improve the accuracy of radiotherapy dose calculations including algorithms for virtual iodine contrast removal. Overall, the project will aim to establish clinical workflows