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Leibniz-Institut für Präventionsforschung und Epidemiologie – BIPS GmbH | Bremen, Bremen | Germany | about 1 month ago
prediction Analysis of primary and secondary data Preparation of reports and English-language publications Presentation of results at conferences The Leibniz Institute for Prevention Research and Epidemiology
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applying systems biology and constraint-based modelling approaches, we aim to capture host–microbiome interactions at a mechanistic level and predict metabolite fluxes relevant to brain health. The project
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Dortmund, we invite applications for a PhD Candidate (m/f/d): Multidimensional Omics Data Analysis You will be responsible for Prediction of metabolic activity in complex microbial communities, leveraging
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techniques. These surrogates will be tuned for rapid, uncertainty‑aware predictions and integrated into decision‑support tools for deep geological repositories of nuclear waste—one of the most pressing
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). These collaborations enable practically relevant and breakthrough results. This team goal requires a quantitative model describing and predicting sperm motility under various conditions. You will develop the digital
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developmental, stem cell and cell biology systems) to predict, observe, and manipulate epigenetic processes. https://www.helmholtz-muenchen.de/ife The Schneider group is recruiting a PhD student to work on the
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of self-assembly for specific types of molecules. Here, we use symmetry and the geometric properties of the molecules in order to calculate bounds that help to predict specific behavior. Moreover, we would
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) to predict, observe, and manipulate epigenetic processes. The Schneider group is looking for a PhD candidate (f/m/x) to work on the interphase between epigenetics and cellular metabolism. The applicant should
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremen, Bremen | Germany | 3 months ago
models as predictive tools to address questions regarding the response of deep-sea ecosystems to various pressures. A key question addresses the best combination of ML and network analysis to maximize
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-driven simulations, optical remote sensing and biogeochemical modeling to predict seagrass distribution under various climate and nutrient scenarios. SEAGUARD aims to provide science-based recommendations