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regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
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systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization
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a doctoral student with a strong background in machine learning, mathematics, and modeling, and an interest in biological systems. The successful candidate will join a project to understand and model
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Are you interested in developing mathematically grounded methods for uncertainty quantification in deep learning, particularly for large language models in healthcare applications? Are you looking
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Bioinformaticians in advanced Machine Learning and AI The Department of Biochemistry and Biophysics. SciLifeLab (SciLifeLab ) is a national center for molecular biosciences with focus on health and
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candidate will be part of the dynamic SciLifeLab community, both locally in Uppsala and across Sweden as a whole. For information on the SciLifeLab Fellow programme, see https://www.scilifelab.se/contact
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machine learning for the next generation of AI models – uncertainty-aware foundation models, generative models and world models – with the support of competent and friendly colleagues in an international
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learning and simulation-based inference for searches for dark matter (or other “invisible” new physics signals) at the Large Hadron Collider, with the support of competent and friendly colleagues in
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the physical mechanisms of infection. We are based at KTH and SciLifeLab in Stockholm (https://hannebellelab.org/ ). We are seeking a PhD student to study the biophysics of schistosome skin infection
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research across various areas, managed under the Department of Immunotechnology. Through the collaborative project L2Bridge, which is supported during five years by a donation (https://www.lu.se/artikel