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the carbon and water trade-offs of forests under different environmental conditions. This particular project aims at the following research objectives: O1: Understanding the impact of drought
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for three consecutive periods (2014-2018 and 2018-2022 and 2023-2026). ICN2 comprises 19 Research Groups, 7 Technical Development and Support Units and Facilities, and 2 Research Platforms, covering different
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here as machine systems that can produce novel and creative results. Several important questions are raised: to what extent are generative AI systems genuinely creative? How do they differ from human and
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of the Earth system at different temporal and spatial scales to improve predictive capability. Comprehensive education: Enjoy numerous opportunities for scientific training, skills development and problem
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mathematical foundation of machine learning models. You will be responsible for developing scientific machine learning methodologies enabling new approaches for solving machine learning problems including
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well as ecological interactions. These data will be analysed to understand similarities and differences between disturbed and undisturbed patches to assess resilience. If feasible, measures of resilience will be
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, diffusion models) to augment microscopy datasets Investigating domain adaptation techniques across different imaging modalities Collaborating closely with experimental partners to validate methods and
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environmental and life sciences challenges. Courses will cover topics such as complexity science, mathematical modelling in evolution, ecology and plant biology, along with transferable skills, including
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). Candidates who are considered to be in conflict with the criteria in the latter act, will not be assessed. You must have an academically relevant background within computer science, applied mathematics
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diagnosis, and therapy of diseases like cardiovascular diseases or cancer. Overall, the institute strives to advance precision medicine by combining knowledge from different fields such as biology, chemistry