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interest in learning, adaptation, and dynamical systems in physical contexts Experience with analytical and\or computational modeling. Proficiency in numerical methods and coding (Python, JAX, MATLAB
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the multi-scale multi-physics nature of the problem, solutions for a reactor relevant operational regime are hard to achieve given slow numerical convergence rates. An employment of fast numerical tools
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mission of unlocking the “geometry of artificial intelligence” then please apply! What you will do Singular Learning Theory (SLT) is a mathematical framework for analysing statistical models that do not
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contribute to a major research project to improve our understanding of macroplastic pollution in coastal seas. Working at the intersection of numerical modelling and observations, you will develop simulations
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Microscopy Center. The project further benefits from excellent dedicated CPU and GPU computing infrastructure to support large-scale numerical modelling and data analysis. This is a full-time, two-year
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, but also to develop approaches to prevent damage. In the project we aim to develop a numerical model to predict root growth. Your task as a Postdoc researcher is to develop a measurement and monitoring
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patterns. You will play a leading role in designing and carrying out numerical experiments, analysing large observational and model datasets, and translating process-level understanding from LES