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PhD Position in Theoretical Machine Learning – Understanding Transformers through Information Theory
, or related fields High motivation for theoretical research Ability to communicate research ideas clearly in both spoken and written English Meritorious qualifications Knowledge of information theory
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modelling at both catchment and road scales, incorporating input from relevant stakeholders.The candidate will gain extensive knowledge in hydrological modelling, climate adaptation, road engineering, and
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at the Division of Fluid Dynamics, within the Department of Mechanics and Maritime Sciences at Chalmers. The project is carried out in collaboration with Vattenfall Research and Development, and is part of
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long-term, and most often global, perspectives on future renewable fuels for transport. We seek to rigorously analyse the feasibility of energy transitions, utilize empirical as well as estimated data
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, 2025 Contact information Associate Professor Peiyuan Chen, Division of Electric Power Engineering peiyuan@chalmers.se, +46 31 772 1639 Assistant Professor Maria Taljergård, Division of Energy Technology
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degree corresponding to at least 240 higher education credits in analytical chemistry, data science, water engineering, or aquatic science Basic knowledge of analytical chemistry and data science
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at the Department of Microtechnology and Nanoscience at Chalmers University of Technology in Gothenburg, Sweden. Project description The continuous miniaturization of silicon-based electronics has driven
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This multidisciplinary research at the intersection of human behavior, engineering, and AI aims to provide the automotive industry with tools to make AVs more appreciated and safer. To fully benefit
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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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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