49 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at Chalmers University of Technology
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, and demonstrated ability to develop computational pipelines for biological datasets. Experience in statistical modeling and/or machine learning applied to biological systems, with the ability to link
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focus for this position should be linked to the learning materiual developed by the lab, but the precise area in focus may depend on the applicants skills. Supervise master’s and/or PhD students to a
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: Educational background: A PhD degree in a field relevant to the project, such as applied linguistics, educational psychology, computational linguistics, psychology/cognitive science with a focus on writing, or
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interest in research team-work Industrial Experience from relevant industries Experience in computer based engineering and/or model based systems engineering tools What you will do Participate as researcher
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Profile Recognised Researcher (R2) Application Deadline 20 Feb 2026 - 22:59 (UTC) Country Sweden Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme
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the new Chalmers Physics and Astronomy Department. The new department will provide a creative and innovative environment for research, learning and outreach. The research team and the AoP division
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Do you want to contribute to exciting research in
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or an equivalent foreign degree in Mechanical Eng., Naval/Maritime Eng., Meteorology, Atmospheric Physics, Chemical Eng., Physics, Mathematics, Aeronautics or any relevant PhD program. This eligibility
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Experience in machine learning Knowledge of SDN and NFV Knowledge of basic TCP/IP protocols What you will do Conduct high-impact research and publish in leading journals and conferences Shape research
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the society and industry, we strive to solve society's major challenges – together. At the Division of Fluid Dynamics , we develop advanced experimental and computational techniques to investigate flows in both