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technology with potentially significant impacts on numerous industrial sectors. At Fraunhofer IKS, we engage in a variety of projects aimed at developing robust and reliable applications of quantum computing
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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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or computational science Strong mathematical skills and interest in developing new mathematical methods Good knowledge of mathematical/numerical optimization methods or deep learning methods Enthusiasm
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) in the Research Group “Numerical Mathematics and Scientific ComputingNumerical Mathematics and Scientific Computing“ (Head: Prof. Dr. V. John) starting as soon as possible. The work tasks include
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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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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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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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linkages based on numerical simulations and to transform them into AI- and ML-ready information to develop and implement an indirect inverse optimization framework to identify microstructures that exhibit
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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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the Research Group “Nonlinear Optimization and Inverse Problems” (Head: Prof. Dr. D. Hömberg) starting as soon as possible. The project is part of a BMBF project concerning industrial scale data preparation