134 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"NORTHUMBRIA-UNIVERSITY" positions in Sweden
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information about us, please visit: www.dbb.su.se . Project description The candidate will develop machine learning (ML) strategies, primarily revolving around interpretable ML and generative AI, to study
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measurement methods (e.g. AFM) or correlative experiments combining mechanical measurements with fluorescence microscopy. It is considered a merit if you have experience in AI-based or machine-learning-based
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• Skills in machine learning and/or decision tree analytical methods, is a particularly strong merit • Experience of research focusing on health care or the health system • Experience of authoring and
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Security, Wireless, and Fixed Networks. The security group has around 20 members. The main research directions are Cryptography, Privacy and System Security for Connected Systems. We are now looking for a
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department is available at: Department-of-computing-science Project description Our societies rely on computer systems and on software stacks. Unfortunately, software systems contain bugs and vulnerabilities
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student in Statistics who can perform high quality statistical research. Apply January 6, 2026, at the latest. We are seeking a PhD student within the WASP-HS project “Machine learning to study causality
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for machine learning, e.g. PyTorch or TensorFlow. Strong ability in spoken and written Swedish. Assessment of the applicants will primarily be based on scientific merits and potential as researchers. Special
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education to enable regions to expand quickly and sustainably. In fact, the future is made here. Are you interested in learning more? Read about Umeå university as a workplace Application deadline 2026-02-27
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education to enable regions to expand quickly and sustainably. In fact, the future is made here. Are you interested in learning more? Read about Umeå university as a workplace Application deadline 2026-02-27
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factor that strongly modifies turbulence, pressure drop, and heat transfer. Unlike conventional machined roughness, AM roughness is characterized by randomness, porosity, and powder adhesion, producing