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performance. Funded by the Swedish Research Council, this research is hosted at the Division of Chemical Physics. About us The research at the division of Chemical Physics at Chalmers University of Technology
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PhD Position in Theoretical Machine Learning – Understanding Transformers through Information Theory
Join us for a fully funded PhD position in theoretical machine learning to uncover how and why transformers work. Explore their inner mechanisms using information theory. As part of this project
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This PhD position offers a unique opportunity to advance safe and transparent control for autonomous, over-actuated electric vehicles. You will work at the intersection of model predictive control
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of robotics, electromobility and autonomous driving. We offer advanced PhD courses where we extend the fundamentals in optimal control, machine learning, probability theory and similar. The research and
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of waveforms for satellite communication and radar systems communication/radar system performance analysis using theory and simulation field tests in relevant operating conditions retrieval of geophysical
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of the PhD student will touch upon various topics multi-body dynamics, optimal control theory, machine learning and robotics and artificial intelligence in general. The focus is broadly upon the development
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related to the research project, including an interest in connecting theory and practice for understanding the relationships between science, politics, power and social justice. Fluent level of English
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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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Project overview This PhD student project focuses on the implementation and utilization of digital tools and technologies to enhance supply chain operations. This involves researching the mechanisms
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these systems operate in, ACPS increasingly rely on data-driven learning-enabled components to perform a variety of challenging decision-making tasks. While indispensable for autonomy, learning-enabled components