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timescales, for various climate states and ice sheet geometries. As training data, precipitation fields from the regional climate model RACMO will be used, which is a leading model in this field and developed
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intuitive links between search parameters and the resulting geometry or performance outcomes. The result will be an LLM-driven framework giving designers clearer cause-effect control over generative shape
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between search parameters and the resulting geometry or performance outcomes. The result will be an LLM-driven framework giving designers clearer cause-effect control over generative shape optimisation. 2
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and establish tighter, more intuitive links between search parameters and the resulting geometry or performance outcomes. The result will be an LLM-driven framework giving designers clearer cause-effect
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Vacancies PhD position on Stochastic geometric numerical methods Key takeaways Are you passionate about developing cutting-edge numerical algorithms at the intersection of geometry, stochastic
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researchers and lecturers, others as technical and administrative support officers. The faculty has a strong international character with staff from more than 70 countries. Together, we work in an informal
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Systems, Differential Geometry and/or Information Theory. Excellent academic credentials. Experience with programming languages (such as Python, Julia, Matlab, C/C++, etc.). Strong knowledge and interest in
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Systems, Differential Geometry and/or Information Theory. Excellent academic credentials. Experience with programming languages (such as Python, Julia, Matlab, C/C++, etc.). Strong knowledge and interest in
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. The KdV Institute offers a stimulating scientific environment in which research focuses mainly within the research programmes (1) Algebra, Geometry and Mathematical Physics, (2) Pure, Applied and Numerical
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to provide input for the Report for Mission Assessment and User Consultation Meetings; supporting work in the modelling of end-to-end performance simulators (scene generators, geometry module, spacecraft