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methods including heat exchangers, heat sink, phase-change materials (PCM), etc. Good written and oral communication skills Proficiency in numeric and analytical skills Ability to work independently and
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activity will focus on the development and application of numerical methods for thermal-hydraulic analysis at both the system and component levels. The work will involve analyzing operating, transient, and
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research tasks, using both analytical and numerical methods, contributing to numerical validation of analytical predictions where relevant; (b) write up results for publication and present them at group
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calculation methods, design-oriented analysis software, and/or general-purpose finite element analysis software for a given verification case. Identify and document comparisons of pertinent analysis output
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, or be awaiting their viva. Ideally, you will have experience with the numerical analysis and computational approximation of PDEs using the finite element method. Experience with degenerate parabolic
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scientific industry. Demonstrated ability to formulate hypothesis and design effective numerical experimental plans. Ability to design and implement new numerical experimental methods. High-level expertise in
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Max Planck Institute for Gravitational Physics, Potsdam-Golm | Potsdam, Brandenburg | Germany | 1 day ago
Relativity (ACR) department at the Albert Einstein Institute (AEI) in Potsdam works across the full chain of that transition — from first-principles modeling of strong-field gravity, through numerical
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project - “Oracle complexity bounds of first-order methods for nonsmooth optimization with nonconvex function constraints”. They will be required to conduct theoretical analysis, algorithm implementation
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for temporal quantum learning. Construct and analyse quantum reservoir-induced kernels and associated finite-sample bounds. Run numerical simulations and benchmarks validating the theory. Publish in leading
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, microplastics; by means of numerical and experimental approaches including high-performance computing, data science methods via machine learning/AI and digital twins, enhancement, development and of application