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Mitigation Policy and Requirements were updated in 2023, with a further update planned for 2030. Addressing this global concern requires not only models capable of projecting debris populations over different
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represent different backgrounds, skills and views. We foster an inclusive culture, as our combined identities, attitudes and ambitions widen our perspective and make up our strengths. Job requirements A PhD
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with scientific programming and quantitative data analysis, particularly in Python, is welcomed. Experience with droplet generation, thermal diagnostics, image processing, or automated experimental
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related field. You have a strong background in numerical modelling and programming (preferably Python). You will collaborate with colleagues who are AeoLiS and CFD specialists, so affinity with
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development, spin simulations, or MR signal modeling is highly desirable. Strong programming skills, for example in Python, MATLAB, C/C++, or a comparable scientific computing environment. Experience with
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including transformers, self-supervised learning, foundation models, autoencoders or related architectures; strong programming skills in Python and experience with a deep-learning framework such as PyTorch
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architectures; • strong programming skills in Python and experience with a deep-learning framework such as PyTorch, including training and evaluating models on GPU/HPC infrastructure; • experience working with
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, for example using Python or comparable tools, and experience with GIS-based spatial analysis. The ability to work with heterogeneous geological, hydrogeological and monitoring datasets and to connect
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; experience with foundational AI model development/fine-tuning and machine learning and/or deep learning; strong programming skills (e.g., Python, JavaScript, PostgreSQL) with clear expertise in front-end and
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, and Den Otter, Weindel, Stuit, Van Maanen, Plos Computational Biology, 2026 for more information about these methods. The goal of the project is to be able to track differences in strategy use between