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, preferably using yeast Genome engineering / synthetic biology, yeast and/or mammalian Cell biology, microscopy, and biochemical approaches Functional genomics and computational data analysis, including AI
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to evaluate strategies aimed at improving health outcomes among people treated in TB programmes worldwide. The position is suitable for candidates at PhD or postdoctoral level and is available for a duration of
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collection (focus groups) in five European countries (DE, IT, NL, PL, UK), as well as data management and analysis Author and co-author papers and publications in the frame of the project and with project
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Profile Master’s degree (for PhD-level appointment) or PhD (postdoc-level), or equivalent expertise in epidemiology, biostatistics, applied mathematics, computer science, biomedical engineering, physics
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survey experiments Engage independently in data collection (survey experiments) in five European countries (DE, IT, NL, PL, UK), as well as data management and analysis Author and co-author papers and
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Oxford Nanopore Technologies (ONT). Your role will be central in creating and applying bioinformatics and machine learning tools to analyze long-read data and decipher cap-specific signals from raw
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where appropriate. Your profile PhD in Immunology, Virology, Infection Biology, or a related field (or near completion). Strong hands-on experience with mouse models; FELASA (or equivalent) is highly