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will have the opportunity to: Gain important insights into clinically relevant aspects of cancer development and therapy Perform state-of-the-art in vivo experiments and large-scale drug and genetic
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analyzing data from large cohorts, ideally within the NAKO German National Cohort Experience in teaching epidemiology to students Desirable qualifications Experience in the field of metabolic diseases
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conferences and the preparation of project reports. Develop and apply software tools. Documentations of software and data according to the FAIR data principles. Contributions to workshops and training
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reports Develop and apply software tools Document software and data according to the FAIR data principles Contribute to workshops and training activities Your Profile: Master with subsequent PhD degree in
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-medicine research groups and big data analyses (statistics) • interest in behavioural biology, animal welfare and laboratory animal science • very good command of English, both written and spoken • a keen
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the integration of large-scale biological datasets derived from both the host and the microbiome, employing advanced statistical methods and cutting-edge artificial intelligence techniques to uncover novel insights
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 2 months ago
environmental factors Your profile Degree in the life sciences & completed doctoral degree in epidemiology Experience in analyzing data from large cohorts, ideally within the NAKO German National Cohort
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central importance for global trade. Much of it is based on the transportation of goods by large container ships. These are not very flexible due to fixed routes, cause environmental problems and are prone
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large multi-dimensional datasets using statistical tools such as positive matrix factorization (PMF) and cluster analysis Investigate the influence of different urban emission sectors on atmospheric
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invasive sensing tools to monitor metabolites, oxygen, carbon dioxide, pH, and other parameters. Ideally, the methods can function in parallel and on a large scale. The research is vital to understand key