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Max Planck Institute for Biological Cybernetics, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | 6 minutes ago
cover letter, CV, and contact information for 2-3 references to robert.ohlendorf@tuebingen.mpg.de .
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to mastering the great challenges facing society today. The Center for Advanced Systems Understanding (CASUS) is a German-Polish research center for data-intensive digital systems research. The Department
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Humboldt Universität zu Berlin / Leibniz Universität Hannover | Hannover, Niedersachsen | Germany | 1 day ago
-qualified candidates with disabilities. Additional information For further information, please contact the scientific coordinator of the RTG2965: Dr. Víctor González-Alonso (email: grk2965@math.uni
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its maintenance and safety increasingly depend on data. This PhD project will develop new methods that combine remote sensing, physics-based modelling, and Bayesian machine learning to support risk
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into the computational environments and data handling routines Presentation of the scientific results on conferences and in publications Applications should be accompanied by a cover letter describing motivation, skills
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experience with methods of molecular biology and/or in the field of histology Experience in animal experimentation is an advantage Knowledge of statistical methods for data analysis Very good written and
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and infrastructure facilities of the Leibniz Association . The DPZ’s Primate Data Science (PRIDAS) platform seeks to fill several positions for PhD candidates in Data Science (m/f/d). The central task
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diseases. You will contribute to the acquisition of multi-omics data from cryopreserved patient-derived samples, working in close collaboration with clinicians to assess patient outcomes. You will present
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using X-ray and neutron scattering. One of the research areas is the development of machine learning (ML) based approaches to efficient analysis of the vast data amounts generated in the scattering
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of molecular and biological matter using X-ray and neutron scattering. One of the research areas is the development of machine learning (ML) based approaches to efficient analysis of the vast data amounts