49 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at Chalmers University of Technology
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28 Feb 2026 Job Information Organisation/Company Chalmers University of Technology Research Field Computer science » Other Engineering » Control engineering Engineering » Systems engineering
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learning-based control within a collaborative and dynamic environment. About us At the department of Electrical Engineering research and education are performed in the areas of Communications, Antennas and
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original research in the area of AI-based program construction or performance engineering, co-supervise one or more doctoral students, teach in the first- and second-cycle software engineering programs
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to applied projects linked to societal needs. Key areas include computational mathematics, optimisation, biomathematics, statistics, and data science, supported by an active PhD programme. Our
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computational costs by orders of magnitude and enabling breakthroughs in drug design and materials science. The position bridges machine learning and molecular science, with opportunities for collaboration
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. The position bridges machine learning and molecular science, with opportunities for collaboration, mentorship, and impactful research. About us The Department of Computer Science and Engineering (CSE
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the last three years prior to the application deadline. Experience in some of the following areas is meritorious: AI and machine learning; convex analysis; functional analysis; mathematical statistics
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Join and help us to derive global forest biomass data from the European Space Agency’s Biomass satellite mission. If you have interests in remote sensing, machine learning and forests, this is the
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the following qualifications: Educational background: A PhD degree in a field relevant to the project, such as applied linguistics, educational psychology, computational linguistics, psychology/cognitive science
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–classical algorithms or optimization methods Background in uncertainty quantification, reduced-order modeling, or machine learning Experience collaborating in interdisciplinary research teams A doctoral