58 data-visualization-analysis Postdoctoral positions at Technical University of Munich in Germany
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, and high-performance computing. It aims to improve the performance of the matrix-free finite-element-based framework HyTeG, in particular by techniques for data reduction through surrogate operators
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will be required to submit personal information. Please be sure to refer to the respective Privacy Policy of each institution. By submitting your application, you confirm that you have read and
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(MUCCnet: atmosphere.ei.tum.de ) Optimization of an urban sensor network configuration for greenhouse gas and air pollutant measurements using mathematical and physical assessments Analysis of ground-based
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of the project is to develop and apply bioinformatic tools for the analysis of high-dimensional immunological data sets. Our laboratory (Zielinski lab) focusses on human T cell regulation in health and disease. We
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(ML4Earth). AI methods, and especially machine learning (ML) with deep neural networks have replaced traditional data analysis methods in recent years. The Technical University of Munich (TUM), together
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- Experience in RNA-sequencing and bio-informatic analysis is a plus - Flexible team player We are offering excellent research conditions, a highly motivated and interdisciplinary team, a friendly working
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: - QUANTITATIVE VERIFICATION: analysis of probabilistic systems (Markov decision processes, stochastic games, chemical reaction networks), automata theory and temporal logic, machine learning in verification
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on the design and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization
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are looking forward to your application, including a letter of motivation describing your skills and research interest, your CV, and contact information for two references. Please send your application
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The Professorship of Public Policy for the Green Transition (PPGT) focuses on designing and evaluating policies for the green transition worldwide. The group uses a variety of methods from automated data analyses