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position / internship in the field of dependable person detection. Your task is to investigate, how reliably different object detection algorithms can recognize and locate persons. This will include 3D
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increasingly important, but also more complex, due to rising demands on performance, precision, quality, and sustainability. Bayesian optimization (BO) - a special machine learning approach - represents a
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The Fraunhofer Institute for Solar Energy Systems ISE in Freiburg is Europe's largest solar research institute. Our approximately 1,400 employees work towards a sustainable, economical, secure, and socially equitable energy supply system based on renewable energies. We contribute to this through...
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models (POPGN and sparse GPs) for uncertainty quantification of complex process Develop surrogate model for multi-stage manufacturing process and use Bayesian optimization (BO) to optimize the output
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Master Thesis on Bayesian Optimization of Multi-stage Processes with Smart Inducing Point Allocation
models (POPGN and sparse GPs) for uncertainty quantification of complex process Develop surrogate model for multi-stage manufacturing process and use Bayesian optimization (BO) to optimize the output
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, communication and mobility. Do you want to contribute to beneficial and meaningful research? Raman spectroscopy is a powerful tool for detecting plant materials in vivo. Our team has already developed methods
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detecting the various constituent materials of an object, thereby aiding in the identification of fraud or defects. What you bring to the table Very good C++ programming skills Strong knowledge in mathematics
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Your Job: The focus of this Master Thesis is the development of an optimization to minimize energy consumption in an existing model of non-road mobile machinery (NRMM). Optimization opportunities will be explored for various powertrain configurations, including conventional internal combustion...
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strategies. Your tasks in detail: Enhance existing Bayesian state estimation with reliability margins using both simulated and, if necessary, real-world grid data. Develop Use-Case-Specific Reinforcement
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and reduction Development and application of big data analytics for large X-ray data sets Application of Bayesian methods to X-ray data Combinatorial analysis of various data from complementary