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with neuroimaging, numerical mathematics, optimization, inverse problems, software development, motivation and research interests. The location for this research will be the workgroup of Prof. Dr
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institutions, and a research and development provider for numerous companies throughout the world. The INM is a member of the Leibniz Association and has about 250 employees. The INM research group
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Knowledge of Matlab, and web-based technologies is of advantage Knowledge in using high-performance compute architectures Experience in implementing and optimizing scientific numeric analysis methods and
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full professor in non-linear PDEs, you will expand and deepen already established connections to other mathematical research groups, such as numerical analysis, geometry, continuous optimization
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assessment, you will develop new, sample-efficient optimal control approaches for gate calibration and test them in numerical simulations. You will pursue your research with the German research collaboration
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optimize and ex-ante evaluate different components of an architecture for improving global public good provision that is sketched here . The architecture consists of two components, tax clubs and reward
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knowledge of energy system modelling or climate modelling Good knowledge of deep learning, PDEs or mathematical/numerical optimization methods Enthusiasm for challenging problems and interdisciplinary
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analysis and visualization Numerical modeling and programming for model optimization & machine-learning What you bring to the table You are studying Simulation Sciences, Mechanical Engineering, Computational
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shape technologies and processes for the future of digital production, packaging and scanning technology, as well as numerous other laser-based applications, including 3D printing and laser fusion
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for electrodes and integrate these models as machine learning-based surrogate models for stack and system-level optimization. Your tasks in detail: Develop automated data processing pipelines to analyze SOC