Sort by
Refine Your Search
-
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
-
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
-
. 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
-
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
-
sensing technologies (camera, Electromagnetic tracking system, FBG sensing) with continuum robotic systems and development of associated sensing and estimation algorithms 3D environment reconstruction based
-
analytical skills. Knowledge about statistical machine learning, robotic perception, multimodal AI algorithms. Proven experience with reinforcement learning algorithms and implementations. Experience in
-
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
-
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
-
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