17 parallel-computing-numerical-methods "Prof" PhD positions at University of Twente in Netherlands
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Vacancies PhD position on Stochastic geometric numerical methods Key takeaways Are you passionate about developing cutting-edge numerical algorithms at the intersection of geometry, stochastic
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Vacancies PhD position in Numerical Modeling of Thermo-Mechanical Effects for High-Performance Mechatronics Key takeaways A PhD position is available at the chair of Precision Engineering at
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design up to phased-array implementations (3 vacancies) With its partners, the University of Twente founded POLARIS, a programme running under the Dutch National Growth Fund (NGF). It realises
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funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Job description Circularity
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total band score of at least 6.5, internet. TOEFL test (TOEFL-iBT) showing a score of at least 90, or a Cambridge CAE-C (CPE). For more information regarding this position, you are welcome to contact Prof
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-driven methods to optimise large-scale renovation flows (Verbouwstromen). By bringing together contractors’ resources, clusters of buildings, and smart operations planning, PRE-MADONA accelerates
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to generate the necessary knowledge and tools to equip local decisionmakers to better deal with conflicting values in parallel transitions and requires an interest in both theory development and engagement with
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from a technical and scientific perspective. The Ph.D. candidate will develop methods for uncovering DNS infrastructure dependencies at scale, relying on active measurements and graph-based analysis
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band score of at least 6.5, internet. TOEFL test (TOEFL-iBT) showing a score of at least 90, or a Cambridge CAE-C (CPE). For additional information, please contact Prof. Dr. Erik Koffijberg
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design, coordination) and non-technical (e.g., streamlined governance and re-engineered processes) natures. The PRE-MADONA project offers a game-changing solution by leveraging data-driven methods