117 high-performance-computing positions at Technical University of Munich in Germany
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and geopolitical issues require a rapid transformation of the system, but many uncertainties remain. Reducing uncertainties is imperative as the scale of investment required is very high and the phase
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that algorithmic parameters are tuned so that the over-approximation of the computed reachable set is small enough to verify a given specification. We will demonstrate our approach not only on ARCH benchmarks, but
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/d) in Energy Informatics. You are passionate about applying cutting-edge information technology to solve the energy and climate crisis and would like to work in a vibrant and international research
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policy, economic sociology, and international relations. Methodologically, it draws on and combines both quantitative and qualitative methods, with a particular focus on computational and multi-method
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to engineering. For more information, visit our webpage www.epc.ed.tum.de/en/mfm. Your profile - M.Sc. degree in chemistry, physics, or informatics (candidates that will soon obtain the degree are also welcome
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industrial relevance Phase change such as vaporization, condensation, melting, and solidification is a first-order phase transition involving latent heat, which is an old topic but has become increasingly
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School of Engineering and Design and maintain strong links with the computer science community. One of our key research areas is the design and operation of intelligent networked production systems
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motivated PhD students, interns, and PostDocs at the intersection of computer vision and machine learning. The positions are fully-funded with payments and benefits according to German public service
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integration of e.g. proteomics, lipidomics, or metabolomics data Requirements: Candidates must hold a master’s degree in Data Engineering, Data Science, Bioinformatics, Informatics, or a related discipline
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diagnosis, and knowledge of the operation of helicopter systems. • Confident handling of Python and common data science tools. • Knowledge of high-performance computing and machine learning. • Fluency in