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study plan. For a doctoral degree, the equivalent of four years of full-time doctoral education is required. The research group Our lab is advancing precision medicine through deep learning models
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application! We are looking for up to two PhD students in Generative AI and Machine Learning Your work assignments We are looking for up to two PhD students working on generative AI/machine learning, with
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PhD Position in Theoretical Machine Learning – Understanding Transformers through Information Theory
Join us for a fully funded PhD position in theoretical machine learning to uncover how and why transformers work. Explore their inner mechanisms using information theory. As part of this project
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of this WASP-financed project is machine learning, in particular dealing with generative models and instabilities associated with cycles of retraining on mixtures of human and machine-generated data
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build the sustainable companies and societies of the future. Our machine learning group is part of the Wallenberg AI, Autonomous Systems and Software Program (WASP). WASP is Sweden’s largest individual
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study programmes to match the skills in demand. We hope that you will help us to build the sustainable companies and societies of the future. The Machine Learning Group at Luleå University of Technology
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, statistical machine learning and deep learning. Rules governing PhD students are set out in the Higher Education Ordinance chapter 5, §§ 1-7 and in Uppsala University's rules and guidelines . About the
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computational methods with a particular focus on deep learning and image analysis. The research is done in close collaboration with the BioImageInformatics Unit of SciLifeLab . SciLifeLab is a national resource
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Sintorn, Professor in digital image processing, at the Department of Information Technology and conducted alongside researchers developing computational methods with a particular focus on deep learning and
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influencing drug efficacy and safety. The project addresses a major bottleneck in drug discovery—metabolite identification, which is traditionally time- and resource-intensive. By leveraging deep learning