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Are you passionate about advancing sustainable mobility solutions? Do you enjoy working at the intersection of artificial intelligence, optimization, and energy management? We invite applications
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Exciting Opportunity in Sustainable Energy Research: Join Us in Advancing Hydrogen Storage Technology! Hydrogen is a critical energy carrier for future sustainable systems. One issue using hydrogen
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technology, Biochemical engineering, Biochemistry, Sustainable production & utilization of marine bioresources, or similar. Equivalent requirements apply to individuals with an education earned outside
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Engineering and Autonomous Systems division . We offer advanced PhD courses where we extend the fundamentals in optimal control, machine learning, probability theory and similar. The research and learning
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, collaborative, and analytical. What you will do Take courses at an advanced level within the Graduate school of Computer Science and Engineering Develop your own scientific concepts and communicate the results
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to optimally prepare it for use in AI-driven systems and solutions. About us The Department of Computer Science and Engineering at Chalmers and University of Gothenburg in Sweden with approximately 300
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of transport. The position will be placed at the Division of Applied Acoustics, Department of Architectural and Civil Engineering . As a PhD student, you will belong to the Graduate School of Applied Acoustics
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PhD Position in Theoretical Machine Learning – Understanding Transformers through Information Theory
environment You will join the Communication Systems (CS) group within the Division of Communications, Antennas, and Optical Networks (CAOS) at the Department of Electrical Engineering . The group includes nine
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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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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