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or neural networks) on CFD data to develop a fast, data-driven wind field predictor. You will combine this surrogate model with AeoLiS and evaluate the accuracy of the new model setup by applying it to
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data to learn contextual representations of microbes and communities and translate them into predictive models for successful crop microbiome engineering. Your job Plant-associated microbiomes can
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Postdoc: AI-driven Urban (Re)Design for Health Faculty: Faculty of Geosciences Department: Department of Human Geography and Spatial Planning Hours per week: 36 to 40 Application deadline: 15
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plant phenotyping, microbiome profiling, predictive modelling and targeted experimental validation to identify the microbial factors that make plants more resilient to disease. Your job You will join the
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-on-modelling-of-tu… Requirements Specific Requirements We seek candidates who are motivated by the proposed research, take initiative to develop ideas, are self-driven, and can work both independently and within
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PhD Position in Generative AI in Health Technology Assessment (HTA) Faculty: Faculty of Science Department: Department of Pharmaceutical Sciences Hours per week: 36 to 40 Application deadline
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Geography, Oceanography, Civil or Hydraulic Engineering, or a related discipline by the time the position starts. Furthermore, you should have: Experience in modelling of sediment transport Coding experience
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a wild, non-model plant species. Your job To face climate change and other environmental challenges, the capacity for rapid adaptation is crucial for both natural plant populations and crops
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candidate with an MSc background in Earth Sciences, Civil or Hydraulic Engineering, or other appropriate fields. You will work on the project: DEEP-FLUX:Journey of low-density particles to the DEEP ocean
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October 2026 Apply now The Department of Earth Sciences is looking for a highly motivated PhD candidate with an MSc background in Earth Sciences, Civil or Hydraulic Engineering, or other appropriate fields