116 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"CEA-Saclay" positions in Sweden
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–experimental feedback loop central to the project. Subject description Recent breakthroughs in deep learning–powered protein design, recognized by the 2024 Nobel Prize in Chemistry, have enabled the creation
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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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. 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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research grants from funders relevant to a Swedish context. Ability to teach courses on adjacent programmes in the department, e.g., software development, human-computer interaction, embedded systems, etc
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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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aspects of software development (DevOps, Algorithms etc.) or informatics (e.g., content design, user experience design and human-computer interaction). You are expected to build and maintain an academic and
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, Intelligent Autonomous Systems, Robot Learning, Machine Learning, Human-Robot Interaction and Natural Language Processing. The division runs, together with the Department for Automatic Control, the RobotLab LTH
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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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to no more than 20% of working hours. The position includes the opportunity for three weeks of training in higher education teaching and learning. The purpose of the position is to develop the independence as a
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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