173 parallel-computing-numerical-methods-"DTU" positions at Technical University of Munich
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, economics, business informatics, data science, or a related field, • with a strong passion for entrepreneurship and/or family enterprise research, • with a solid knowledge of empirical research methods
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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 methods
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, or learning sciences. You are interested in interdisciplinary collaboration and working in research teams. You have very good knowledge of social science research methods and statistics. You have
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failure mechanisms. The performance of the developed methods will be evaluated using real operating data. In addition, it will be investigated how reliability and safety conditions can be taken into account
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research methods and statistics. - Experiences with research syntheses (e.g., meta-analyses) and video data analyses would be an advantage. - You have very good written and spoken Eng-lish skills and good
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investigations carried out on the research compressor by an integrated team of LTF and an industry partner. - Numerical modelling compressor stages and carry out simulation of methods to enhance aerodynamic
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(https://soilsystems.net/ ), a Priority Programme (SPP 2322) funded by the Deutsche Forschungsgemeinschaft (DFG; German Research Foundation). Within SoilSystems, scientists from different disciplines from
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and industry insights. The candidate will be expected to: Apply advanced analytical and AI methods to solve real-world operational challenges. Publish in leading journals and present research
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PostDoc (m/w/d) position on “Biological engineering of novel gene reporters for Electron Microscopy”
the systematic analysis of function-ultrastructure relationships in brains with implications for our understanding of neuropsychiatric diseases and inspiration for neuromorphic computing. Your Ideal Qualifications
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empirical research with design practices from a comparative perspective. CUSP aims to approach urban and peripheral spatial research through ethnographic and qualitative methods. We focus on the critical