131 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"ISCTE-IUL" positions in Sweden
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. Our research is focused on cell biology, spatial proteiomics and machine learning for bioimage analysis. The aim is to understand how human proteins are distributed in time and space, how this affects
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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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• 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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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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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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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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completed their doctoral degree prior to that may also be eligible. Special reasons include absence due to illness, parental leave, appointments of trust in trade union organisations, military service
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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