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for emulating high-resolution process-based land-surface models - Combine process-based land surface and vegetation model components with data-driven model parts, e.g. in the framework of Neural Differential
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and scientific articles the supervision of PhD and master students Your Profile: Completed academic university degree with subsequent PhD in physics, computer science, mathematics or comparable fields
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Package: Actively participate in a participant-driven co-design process to develop a framework for returning molecular and imaging data to study participants Contribute scientific content to patient
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 3 months ago
PhD in computer science, mathematics, physics, bio-/medical informatics or related fields, specializing in image analysis or machine learning, proficiency in deep learning techniques (CNN, VIT
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adaptive systems that jointly optimize morphology and control for real-world physical interaction. Requirements Ph.D. in Computer Science or a related discipline. Strong background in Machine Learning
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include mentoring graduate and undergraduate students and contributing to the development of grant proposals and project reports. Requirements: PhD degree in materials science, physics or closely related
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | 2 days ago
understanding of socio-economic inequalities. (PIs: Gummadi, Cha, Zagheni) As agentic AI integrates human workers into automated workflows, it becomes important to understand the AI-human matching process under
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international collaboration partners Support and administer internal web and Linux servers Your Profile Academic degree (master's and Ph.D.) with a background in computer science, bioinformatics, physics
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | 3 months ago
model on observations and physical models to represent cloud processes across scales from individual turbulent eddies to cloud systems spanning hundreds of kilometers. We will use this fully data-driven
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chaperones and the question how membrane protein chaperones recognize and process clients on a molecular level. The project has the potential to provide exciting new insights in the molecular biology of cells