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: Mathematics, Mathematical Statistics and Computational Mathematics. The research at the Division of Computational Mathematics covers many different areas in numerical analysis, symbolic computations
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year project, funded by the DDLS program, we aim to develop AI-based tools in design of affinity ligands, such as the prediction of binding interactions between proteins. Data-driven life science (DDLS
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description The project focuses on studying the evolution of evolvability using computational simulations. Evidence from evolutionary developmental biology suggests that evolvability can change rapidly in
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the Royal Institute of Technology, Stockholm. Dahlin’s team works at the intersection between experimental and computational medicine to map blood cell development at the single-cell level. This is performed
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Are you passionate about applying computational approaches to solve problems in biomedicine? We are now looking for an Industrial PhD student in Data-Driven Life Sciences to work on a cutting-edge
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vision, machine learning, deep learning and neural networks, as well as courses in python, GPU programming, mathematical modeling and statistics, or equivalent. We are looking for candidates with: A solid
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of image analysis and machine learning with a minimum of 90 higher education credits. Relevant courses include, for example, image processing, computer vision, machine learning, deep learning and neural
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interdisciplinary backgrounds and expertise to foster cutting-edge research with high clinical relevance. Project Description Imaging methods such as magnetic resonance imaging (MRI), computed tomography (CT), and
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will combine state-of-the-art computer vision, modeling and archived specimens to determine biotic and abiotic factors driving spatial variation in molt phenology. It will use museum genomics to recover
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) program. Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular