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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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components of organisms’ general life-history decisions. The work involves accumulation of mutations in different fly lines, extracting DNA and building libraries for sequencing, as well as bioinformatics
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substantially equivalent knowledge in some other way. For this position, the applicant must hold a master’s degree in molecular biotechnology, bioinformatics, computer science, or another area that the employer
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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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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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consequences of higher host specialisation in the tropics – the role of ecological and evolutionary processes, and of data bias), and the successful applicant will work in the Evonets lab (evonetslab.github.io
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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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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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(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 global
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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