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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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research environments in Computational Science, the research and education has a unique breadth, with large activities in areas such as numerical analysis, mathematical modelling, development and analysis
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and variation. The successful candidate will develop innovative methods and models to advance our understanding of genome evolution and variation. The position is based in the Computational Genomics
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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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KTH Royal Institute of Technology, School of Engineering Sciences Job description The AICell Lab (https://aicell.io ) in the department of Applied Physics at KTH and Science for Life Laboratory is a
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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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Join ABC Labs and KTH as an Industrial PhD Student to build data-driven models of human biology with multimodal health data — interdisciplinary impact, real-world healthcare. About the role We
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, mathematical modeling and statistics, or equivalent. We are looking for candidates with: A solid academic background with thorough computational and analytical understanding; Proficiency in programming in Python
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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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an outstanding and ambitious postdoctoral researcher in computational biology to pioneer understanding and modeling of tissue architecture using single-cell and spatial transcriptomics data. The focus will be