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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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team that combines engineering and the humanities? Then apply for the PhD position on Explainable AI in Machine Vision for autonomous driving! Autonomous driving is a key application of artificial
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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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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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systems on random graphs by rigorously characterizing the set of Gibbs measures. Applications of such problems range from computational complexity, coding theory, to machine learning. This PhD project
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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
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network and data centers, the transmission link optimization at the physical layer, and the computing decentralized systems by exploiting state of the art machine learning approaches to ultimately implement
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people's daily lives. Job requirements This work is at the intersection of between moral philosophy, human-computer interaction and industrial design. Candidates should have a master’s degree in a related
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Revolutionize neuroscientific visualization with real-time cinematic tractography. Join our innovative PhD project to develop cutting-edge brain visualizations, bridging the gap between data
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processing pathways to electro chemically upcycle pyrolysis carbons into value added graphene(oxide) colloids. Your PhD project is part of a larger collaboration between TU Eindhoven and Shell on