24 high-performance-computing PhD positions at Chalmers University of Technology in Sweden
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PhD Position in Theoretical Machine Learning – Understanding Transformers through Information Theory
performance in core mathematics and machine learning courses Master’s degree (or near completion) corresponding to at least 240 higher education credits in mathematics, computer science, electrical engineering
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We are looking for a highly motivated, skilled, and persistent PhD student with experience in computational fluid dynamics (CFD) and some knowledge in structural analysis. The research aims
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This is a broad call for five fully-funded PhD positions in computer science and engineering to work on machine learning, autonomous systems, software engineering, formal methods, and network
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operation Quantum algorithm implementation and benchmarking About you You have a relevant Masters deegree corresponding to at least 240 higher education credits (Physics, Nanotechnology, Engineering, Computer
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on developing novel memory and logic devices based on TMDs. These will target both near-term industrial applications and emerging neuromorphic (brain-inspired) computing architectures for AI accelerator hardware
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will be part of a dynamic and inspiring working environment in the beautiful city of Gothenburg on the West coast of Sweden. About us The Department of Computer Science and Engineering is a fully
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will perform computational modeling of perceived safety and comfort zone boundaries based on in-project data collection from drivers. The modeling will be both rule- and machine-learning/AI based
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learning, data integration, and model evaluation in collaboration with industry partners for real-world impact. About us The Department of Computer Science and Engineering at Chalmers and University
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to operate around the clock. By ensuring the performance, longevity, and circularity of industrial systems such as advanced manufacturing (e.g., automotive and battery) and renewable energy (e.g., energy
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develop robotic fabrication workflows for 3D printing to fit uniquely shaped components waste-free and with high design quality. About the research environment The PhD student will join the research area