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Field
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, with a clear path to methodological and applied impact in healthcare. Your qualities A Master’s degree in epidemiology, (bio)statistics, health data science, or a related discipline; a strong foundation
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Leibniz-Institute for Food Systems Biology at the Technical University of Munich | Freising, Bayern | Germany | about 1 month ago
appetite regulation, caloric intake, and overall health outcomes. To explore this hypothesis, we will integrate a combination of mechanistic in-vitro studies and population-based epidemiological research
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outcomes. To explore this hypothesis, we will integrate a combination of mechanistic in-vitro studies and population-based epidemiological research. Researchers on this project will benefit from a
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ecological zones spanning rural, peri-urban, and urban epidemiological settings in Djibouti, Ethiopia, Kenya, and Nigeria, with the aim of pinpointing factors driving invasion. You will work closely with our
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limited to: International/Sustainable Development Geography/Environmental Studies Social Sciences Public Health/Epidemiology Psychology/Mental health sciences Education Climate Science Sociology
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following skills and experience: Essential criteria Master's degree in a relevant area of the social sciences (e.g. Mental Health Studies, Public Health, Epidemiology, Occupational Health, Research Methods
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for candidates to have the following skills and experience: Essential criteria Master's degree in a relevant area of the social sciences (e.g. Mental Health Studies, Public Health, Epidemiology, Occupational
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comprehensive databases combining nationwide Norwegian health and socioeconomic registry data, biobanks and patient-reported data. Using advanced epidemiological methods, causal inference and machine learning
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restoration. In DIGDEEP, we combine large-scale ecological experiments with epidemiological modelling to uncover general rules of disease transmission in plant communities. As our PhD candidate, you will take
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to detect and respond to emerging respiratory viruses. ANTICIPATE aims to strengthen pandemic preparedness by developing AI-driven tools and epidemiological models to (1) detect novel pathogens early through