20 computational-science PhD positions at Chalmers University of Technology in Sweden
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of the technology in the companies in Software Center. About us The Department of Computer Science and Engineering at Chalmers and University of Gothenburg in Sweden with approximately 300 employees from more than
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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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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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for Quantum Technology (WACQT, http://wacqt.se ). The core project of the centre is to build a quantum computer based on superconducting circuits. You will be part of the Quantum Computing group in the Quantum
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technology, building physics, HVAC systems, computer science and control systems architecture, thereby advancing all disciplines involved. The project is a collaboration with Building Services Engineering
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What does policy and practice for recruitment to university STEM (Science, Technology, Engineering, and Mathematics) education look like, and what are the consequences for equality and social
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in the management of technology, people, and organization, and a desire to make groundbreaking contributions to the field of maintenance engineering. PhD Project overview The project focuses
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: The successful candidate must have a Master's degree in electrical engineering, engineering physics, or related disciplines. Completed courses in signal processing, radar or communication theory are meritorious
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computational tools developed by our research team for addressing a timely societally relevant problem. Project overview The aim is to unravel the anthropogenic and natural processes, and their relative
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. The applicant should have strong background in mathematical foundations of computer science and experience in Python programming. Previous experience in deep learning, reinforcement learning, or explainable AI is