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degree in relevant fields (bioinformatics, immunology, computational biology, mathematics, and/or statistics). Strong programming skills in R and/or Python Demonstrated strong ability in analyzing high
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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
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research school. 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
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different aspects of evolvability – the ability of organisms to evolve. We are interested in developing computational and mathematical tools to understand and quantify evolvability while exploring its
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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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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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. To meet the general entry requirements for doctoral studies, you must: Hold a Master’s degree in computer science, image analysis and machine learning, engineering, data sciences, applied mathematics
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at developing and applying computational tools to understand the evolution of biodiversity (see https://islandevolution.github.io/ ). As a postdoc in this project, you will work with mathematical modelling
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in computer science, engineering, data sciences, applied mathematics, machine learning, or another related field; or Have completed at least 240 credits in higher education, with at least 60 credits at
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science. We are looking for a candidate with a PhD in either engineering/computer science/physics/mathematics. Experience with ML implementation (ideally interpretable ML and/or generative AI) is required