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biomedicine, biomolecular technology, and biodiversity converge working synchronously under one roof. With one of the highest concentrations of bioinformaticians and computational biologists in Europe, Campus
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to receiving your application! 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
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the national Data-Driven Life Science (DDLS) program. About the position and the project As an industrial PhD student, you will be employed by the startup company PredictMe AB while being formally enrolled as a
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-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 processes to human
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programme. The doctoral programme comprises 25 credits and is offered in two study variants: 25 credits spread over 8 terms (a total of 4 years) or over 12 terms (a total of 6 years), starting each autumn and
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effects. Importantly, computational predictions will be directly linked to experimental evaluation of GalNAc-conjugated RNA therapeutics. This position offers a unique opportunity to work in a highly
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to improve the interpretation and matching of mass spectrometry data, a field in which Sweden holds a leading global position. To this end, the doctoral student will use and develop computational tools, and a
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science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and
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epidemiology and biology of infection, which is a fully funded, four-year PhD student position. Data-driven life science Research School Data-driven life science (DDLS) uses data, computational methods, and
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omics. To achieve this, the doctoral student will use and develop both computational and laboratory-based tools. The doctoral student will need a background that includes experience with both some