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Field
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processes that produce energy and raw materials. The Department of Thermodynamics of Actinides is looking for a PhD Student (f/m/d) - Machine Learning for Modelling Complex Geochemical Systems. The job
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of heat transfer and turbulence physics in wall-bounded flows through numerical simulations, data-driven modelling, and machine learning techniques. Key goals include optimising convective heat transfer
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to constrain the depth of the magmatic pressurization source (5). Training The candidate will gain skills in seismic data processing, tomographic imaging, and numerical modelling. Travel opportunities include
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profound interest in inorganic chemistry, both in experimental and modelling applications. We are looking for candidates who are also interested in the analytical and numerical aspects of the work
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evaluation of efficient training and reconstruction pipelines involving deep learning models Find required initial conditions for LWFA simulations which yield the reconstructed observed electron buch shapes
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the development of a phase-field model to study the mechanisms of formation and growth of tetrataenite (Ni-Fe with the L1₀ ordered structure) during cooling. The objective is to incorporate the presence
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provide powerful tools to improve the quality and efficiency of data-driven models. In parallel to the development of data-driven models for dynamical systems with geometric structures such as Hamiltonian
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Collaborative Doctoral Project (PhD Position) - AI-guided design of scaffold-free DNA nanostructures
nano-structures. In this project, we will combine numerical models, experiments, and artificial intelligence (AI) to guide the design of specific DNA nanoconstructs. The primary goal is to build an AI
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. The objective of the thesis is to have a theoretical and numerical model of a free-surface flow on an erodible bed, satisfactorily explaining two documented historical cases of flooding by river dike failure
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numerical methods and strategies to solve the electromagnetic and heat transfer problem in induction welding. Develop constitutive models that capture the temperature dependence of anisotropic