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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 processes
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of MSI advances our understanding of complex brain processes. The prospective PhD candidate collects brain MSI data and develops novel machine learning methods in connection to generative models such as
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synthesis process conditions to maximise the drug loading. We will start with passive nanocarriers (e.g. Calcium Phosphate) and move one to active nanocarriers, such as Cerium oxide or Gallium-based
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natural mixtures to be explored in much better depth using pure standards. The results of ongoing work in the research group will be used to better understand how Earth’s ecosystems process carbon compounds
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) programme and 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
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. The data-driven life science initiative Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular
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drug development with the mission to translate academic discoveries into drug candidates for further commercial development. The operation, which has been in place for ten years, has contributed to 15
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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 health
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identify systems-level mechanisms in cancer that can be used to uncover new biomarkers, drug targets, and paths to drug resistance. The long-term goal of our lab is to enable computer-aided design of
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structures and their dynamics to characterise the function and structure of key reaction intermediate will allow you to truly elucidate the processes of H2 catalysis in [FeFe]-hydrogenases and N2 reduction in