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motivated and skilled PhD candidate to work in the area of probabilistic machine learning. The position is fully funded for a term of four years. The research direction will be determined together
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computing (SC)? Are you fascinated by the emerging field of machine learning (ML)? Are you our next PhD-candidate in scientific machine learning or SciML (combining SC and ML)? Are you eager to work on the
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of the vertices in multi-dimensional space for machine learning tasks. Policy evaluation is widely used in reinforcement learning, for instance, for training large language models. Your challenge is to develop
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machines are commonly used in electric vehicles. However, these machines have several disadvantages, such as the high cost of the permanent-magnet (PM) material and decreased performance at higher
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of machine capabilities. However, learning these models requires direct access to vast data repositories, which poses significant privacy and logistical challenges, especially in the health sensing domain
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. This PhD project is designed to identify, systemize and evaluate XAI methods, and to identify best-practices for machine vision in the context of autonomous driving, while taking into account human factors
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Motivated researcher, with a PhD in Mathematics, Computer Science, or related discipline(s). Ability to conduct high quality academic research, reflected in demonstratable outputs. Ability to teach
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of challenge, why not join us? We are looking for someone to take on a PhD position focusing on learning analytics-based dashboards at the Human-Technology Interaction Group (HTI) within the School of Innovation
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Position PhD-student, (Post-doctoral) Researcher Irène Curie Fellowship No Department(s) Electrical Engineering Reference number V36.7438 Job description The Electrical Energy Systems (EES) group
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surrogate models. Applying symbolic reasoning to define and analyze system components and their interactions. Merging machine learning with symbolic AI to enhance system (performance) monitoring. Advancing