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biology, molecular biology and animal models to investigate how these hybrid cells favour carcinogenesis. Where to apply Website https://app.smartsheet.au/b/form/019eedeef91978fdbc2b67718479eac6?project_id
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About the lab The Laboratory of Causal Systems Immunology combines large-scale in vivo perturbation experiments, advanced mouse models of immune diseases and causal learning to uncover how genes
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muscle cells remains largely unknown. Using human vascular cell models, the student will investigate whether loss of endothelial PKD1 alters smooth muscle cell behaviour, including changes in cell
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Committee. With approximately 180 members, EconomiX is one of France's leading centers for economic research. Its research activities are organized around three main areas: • Transitions, Environment, Energy
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Committee. With approximately 180 members, EconomiX is one of France's leading centers for economic research. Its research activities are organized around three main areas: • Transitions, Environment, Energy
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 7 hours ago
pathways in cellular and mouse models of metabolic diseases You will perform biochemical and cell biological characterization of protein localization and organelle interactions You will apply and further
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chemistry, theory and modelling, fundamental materials physics, and device development, with applications in energy, printed electronics, photonics, and bioelectronics. A strong common theme is materials
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foundational methods for integrating single-cell and clinical transcriptomes; and train, fine-tune, and validate deep learning models using multi-omics and imaging data to predict clinical outcomes such as
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Posting Details Posting Details Job Title Director of Energy Systems Modeling EPIC Requisition Number RE55299 Working Title Department Name 40550:Ctr For Applied Energy Res Work Location Lexington
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learning, epigenomic data, and mechanistic modelling. The mission is to contribute to the development of predictive models of the replication initiation probability landscape (IPLS) from limited experimental