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the project include mathematical derivation, analysis, and comparison of models, methods, and simulation approaches; rapid prototyping of new ideas in custom code; implementation of new models, methods, and
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] Subject Areas: Applied Mathematics, numerical methods, simulation and modelling Appl Deadline: 2025/05/31 11:59PM (accepting applications posted 2025/02/13) Position Description: Position Description
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/forschung/gruppen/numerical-analysis/research/ Typical responsibilities you can expect: Mathematical derivation, analysis, and comparison of models, methods, and simulation approaches Formal proofs, e.g
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' prognosis or treatment decisions. For modeling, we use both public and proprietary clinical and research data greatly enriched by our own repository of digital pathology images. A further focus lies on
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related field at the time of appointment Required knowledge Excellent knowledge of spaceflight mechanics, control, orbital robotics, and space systems engineering Excellent mathematical, analytical and
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to 2 years; an extension of an additional 2 years is possible. TASKS: Mathematical and physical modeling to determine greenhouse gas and pollutant emissions in cities using novel atmospheric measurements
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focus on deep networks for solving inverse problems, learning robust models from few and noisy samples, and DNA data storage. The position is in the area of machine learning, with a focus on deep learning
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14.12.2022, Wissenschaftliches Personal The BMBF-funded position is part of the CoMPS project, which is a multidisciplinary project combining the fields of mathematics, computer science, geophysics
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. For modeling, we use both public and proprietary clinical and research data and generate our own repository of digital pathology images. A further focus of our lab is the improvement of digital pathology
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communication system are modeled using information theory. We wish to investigate how interleaving can reduce the overhead and computational load due to coding coefficients required in classical linear random