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Qualifications / Experience: • A PhD in Physics, Geoscience or a related field • Proven expertise in numerical modelling using super computing clusters • Excellent knowledge of atmospheric physics • Proficiency in
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Max Planck Institute for Biology Tübingen, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | about 2 hours ago
, computational biology, and genetic engineering strategies to drive these goals. The Group is within the Department of Microbiome Science, led by Prof. Ruth Ley. The project Methanogens are abundant, diverse, and
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Join our team as a Early-Career PostDoc (m/f/d) in the research area of AI‑based modelling full-time (39.2 hr/week), fixed term for two years. Leibniz-IWT stands for research in the field of new
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employ state-of-the-art experimental models to study the pathomechanism of severe congenital neutropenia and Shwachman-Diamond Syndrome as well as the stepwise process of leukemogenic transformation. Our
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, molecular biotechnology and computational sciences. The modern Campus harbors the buildings of the science faculties and institutes, in direct vicinity to the University Hospital Heidelberg, the Max Planck
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alters immune responses against vaccines using next-generation human tissue and organoid models. Current vaccines against infectious diseases and cancer benefit only a subset of patients, partly due to our
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Max Planck Institute for Nuclear Physics, Heidelberg | Heidelberg, Baden W rttemberg | Germany | about 2 hours ago
Hinton ) at the Max Planck Institute for Nuclear Physics in Heidelberg (Germany) offers Postdoc positions (m/f/d). The Division is engaged in a broad programme of experimental and observational activities
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environment in the fields of science, technology and administration as well as for the education of highly qualified young scientists. The computational imaging group at DESY is concerned with the development
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, predict, and treat diseases. You will work with multimodal biomedical datasets including omics, imaging, and patient data and apply cutting-edge AI models such as graph neural networks, transformer
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numerical fluid mechanics, scientific computing, or model-order reduction, who is willing to engage in innovative and interdisciplinary research questions. The successful candidate will also have the