20 parallel-programming-"Multiple"-"Humboldt-Stiftung-Foundation" PhD positions at Utrecht University in Netherlands
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-of-the-art implementations of these new techniques (e.g., by leveraging data-parallel functional array programming techniques); applying them to solve real-world problems (e.g., gradient estimation challenges
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are encouraged to submit a research proposal that aligns with UCALL's research programme and encompasses multiple areas of law. Your job Over a period of four years, you will conduct a PhD research under the
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and AMOC changes at decadal to millennial timescales. This project may include participation in seagoing expeditions. This project is part of the 10-year EMBRACER research programme funded by the Dutch
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and is affected by various biogeochemical processes. The processes governing ocean alkalinity act over multiple timescales (from instantaneous chemical equilibration to hundred thousand of years) and
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that complement your work. A personalised training programme will be set up, reflecting your training needs and career objectives. About 20% of your time will be dedicated to this training component, which includes
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. You already have good background knowledge on atmospheric composition and greenhouse gas cycles and experience with isotope measurements. Next to this you find yourself in one or multiple
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engineering challenges, and are motivated by contributing to the advancement of scientific knowledge. Furthermore, you bring multiple of the following qualifications: Scientific and Technical Competence You
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methodology through an integrated research programme across geoinformatics, AI, and geography. The project is based at the Department of Human Geography and Spatial Planning, Utrecht University, and contributes
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part of the ERC-funded project GeoTrAnsQData, which develops the foundations of a transformative GeoQA methodology through an integrated research program across geoinformatics, AI, and geography
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in the SPG. We will make use of models of different complexity up to complex Earth System models, and modelling efforts for different past periods. A personalised training programme will be set up