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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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04.02.2026, Academic staff The successful candidates will be part of the Munich Climate Center and the Earth System Modelling group at TUM (https://www.asg.ed.tum.de/esm/home/) and will be closely
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volume correlation processing of images in preparation for image-based modelling Your profile PhD in physics, materials science, computer science, applied mathematics or a related field strong background
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. Within this project, work package 1 focuses on the resilience of the marine sinks of heat and carbon, using Earth system and biogeochemical models, observational data, and scenario analysis to identify
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. Within this project, work package 1 focuses on the resilience of the marine sinks of heat and carbon, using Earth system and biogeochemical models, observational data, and scenario analysis to identify
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | 3 months ago
pipeline, building on existing deep learning models in meteorology and climate science Your Profile PhD in computational science, mathematics, physics, or a related subject Experience with machine-learning
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Gorlitz, Sachsen | Germany | 3 months ago
generative AI models (e.g., VAEs, GANs, Diffusion Models) to create novel protein sequences, fold structures, and functional molecules # Engage with our international collaborators (Berlin, Dresden, London
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focuses on the resilience of the marine sinks of heat and carbon, using Earth system and biogeochemical models, observational data, and scenario analysis to identify early-warning signals and tipping points
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 3 months ago
, improving lives. The Horvath Lab at the Institute of AI for Health (AIH) aims to build large deep learning models for digital pathology to resolve single cell heterogeneity and identify subtle cellular
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Research Centre (CRC) 1450 “inSight – Multiscale imaging of organ-specific inflammation” (https://www.uni-muenster.de/CRC-inSight) The project is based in the research group of Prof. Dr. Kerstin Steinbrink