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Field
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part of a DFG funded project "Decoupling above- from belowground litter decomposition and impacts on stabilization of soil organic matter with increasing aridity". Drylands cover large areas of the land
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Your Job: As part of an interdisciplinary team, you will develop approaches for the automated and large-scale provision and integration of energy systems data and models and apply data science
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correlation structures across data modalities that relate to outcomes such as survival and treatment response. Validation & Benchmarking: Apply the framework across cancer types, evaluating various foundation
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analysis problems, especially tracking the motion of objects, which are driven by real applications in life science research Developing solutions to integrate large foundation models into microscopy image
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hole or neutron star orbiting at a large distance from a ‘normal’ companion star. This is a very long-lived state which accounts for the vast majority of the millions of binary systems harbouring neutron
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This large-scale ecological project investigates the barriers and drivers of post-fire forest recovery. With climate change and the spread of forest fires to new areas, it is important to
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Senior Researcher in Synthetic Biology and Metabolic Engineering of power-to-X utilizing Microorg...
the potential of biological systems. Big data approaches and analysis of biological systems are key research instruments at the Center. DTU Biosustain utilizes these advances for microbial cell factory design to
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research opportunity focuses on advancing large-scale additive manufacturing using metal wire as feedstock and electric arc as the heat source. The project aims to develop an innovative and efficient method
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cyanobacteria and Paramecium bursaria. Image data analysis using AI-based tools and programming analysis scripts. Participation in conferences, presentations, and preparation of publications. Intensive exchange
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you eager to make AI more sustainable? As a PhD Candidate, you will develop innovative methods for predicting and reducing the energy consumption of large-scale AI systems during their design phase