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-climatic Extremes (GENAI-X)«, funded by the Carl-Zeiss-Stiftung, addresses a fundamental AI challenge: achieving robust model generalizability in non-stationary environmental systems. Focusing on hydro
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mineral and metal-bearing raw materials more efficiently and to recycle them in an environmentally friendly way. The Group Geometallurgy and Particle Based Process Modelling is looking for a PhD Student (f
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agroecosystem model simulations. The successful candidate will play a key role in developing robust landscape-scale digital twins and advancing data assimilation techniques for agricultural and environmental
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for sustainable agriculture. PhenoRob’s mission is to transform crop production by optimizing breeding and farm management through innovative sensing technologies, advanced modeling, and intelligent automation
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nuclear genome, between cells in one organ, between its roots and above-ground organs, with related plant species and their genomes, with microbes and other biota, and with abiotic environmental factors. We
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24 Nov 2025 Job Information Organisation/Company University of Regensburg Department Faculty of Biology and Pre-Clinical Medicine Research Field Environmental science » Ecology Researcher Profile
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nuclear genome, between cells in one organ, between its roots and above-ground organs, with related plant species and their genomes, with microbes and other biota, and with abiotic environmental factors. We
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | 15 days ago
journals Collaborate closely with project partners on data synthesis and ecosystem modelling Your Profile M.Sc. or diploma in environmental sciences, marine biogeochemistry, or a related discipline Very good
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of the downstream expansion behaviour of the engine exhaust plume for different atmospheric layers. Definition of suitable interfaces to process data for the climate models. Expected Results: Ability to assess
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and as part of a team Understanding of dynamical systems, time series models, machine learning, Bayesian statistics, experience in handling environmental and climate data is a merit We offer: This