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algorithmic approaches to assess their suitability for solving the global problem in terms of convergence, characterisation of correlations, and false positive detection, which is particularly important for
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, and false positive detection, which is particularly important for fainter sources. An additional aspect is multi-messenger science and we wish to investigate the use of external data (e.g. from Gaia
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data collection, integration, and modelling and 2) co-constructing case studies to demonstrate how this workflow may be applied at the local scale but also integrated internationally. This postdoc
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science-related applications. Explicitly accounting for symmetry is not the standard approach in machine learning – a well set up model should be able to ‘detect’ the symmetry automatically. One way
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within material physics, primarily theory and modelling of atomically laminated materials. We will use open data bases and high-throughput simulations to explore a wide range of known and hypothetical 2D
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team effort to develop modelling of the Novatron concept for stable plasma confinement. The Novatron is a new improved type of mirror device. A particular goal of the postdoctoral project is to develop
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the simulation of microbubbles. Microbubbles can for example be used to transport drugs to the desired location in the body. We will develop a surrogate model that can be used to effectively scale up
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with a human-centric, sustainability-driven approach. The Postdoctoral researcher will work on using AI-powered methods, testing, and simulation technologies for the verification and validation
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transport measurements. In addition, the project involves data analysis, data simulations, writing reports (scientific articles and project documents), and oral presentations at European project meetings and
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magnetocrystalline anisotropy. Working on the interdisciplinary VR project offers a unique opportunity to be part of a diverse research team that spans materials modelling and experimental work. For more details about