57 parallel-computing-numerical-methods research jobs at Technical University of Munich
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Methods, LBM), and HPC. For a selection of possible research areas, see: https://www.math.cit.tum.de/math/forschung/gruppen/numerical-analysis/research/ Responsibilities: Development and analysis of new
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Informatics Initiative (MII)/FHIR standards Design and implement methodological concepts and software for benchmarking frameworks for AI evaluation Independently develop and implement research ideas within
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. In the ELUD research project, we address the question of if and when learning agents converge to an efficient equilibrium and when this is not the case. ELUD will design new algorithms for computing
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-making. Experience with computational modeling, especially dynamic models such as drift-diffusion modeling, and eye tracking is expected. Strong skills in experimental methods, quantitative analysis
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applying computer science methods within the context described above. In particular, you will coordinate the contributions of the professorship to the EU project INTELLIGENT (https://intelligent-project.eu
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use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission analysis, and infrared thermography. Industry
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: PhD in CS/ML/medical informatics, strong publication record, and hands-on experience with generative models in medical imaging. Postdoctoral Research Associate (f/m/d) EU Research Project TWIN-X Full
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the application of AI methods in engineering. Description: Nowadays, computer-aided manufacturing (CAM) methods are used to a large extent for the production of complex machine components, in which NC
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, structural biology methods Expertise with computational workflows, scripting, or data analysis Excellent organizational, communication, and project management skills, ability to work interdisciplinary and
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Chair of Biological Imaging 10.02.2026, Academic staff We now seek a highly qualified and motivated Post-doctoral researcher (f/m/d) to drive the development of methods for optoacoustic data