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EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Start date: September 2026 (flexible) Duration: 3 years (36 months) Project The High Performance
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The Department of Biomedicine at Faculty of Health at Aarhus University invites applications for one or more Postdoc positions in the field of Environmental toxicants in Parkinson’s disease as per 1
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to computational materials, mechanics, or related fields Proven ability to work collaboratively in an interdisciplinary research environment and mentor graduate students. Experience with high-performance computing
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that such institutions must be the recipient of a PREP award. The PREP program requires staff from a wide range of backgrounds to work on scientific research in many areas. Employees in this position will perform
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, and physics based computational modeling of joining processes or performance of welded structures. As a postdoc, you will conduct research and development at the forefront and often at the intersection
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Bingen am Rhein, Rheinland Pfalz | Germany | about 7 hours ago
.“ Get to know us Benefits Career Development: Postdoc program, scientific training & career center with tailored offers Scientific Resources: State-of-the-art infrastruture and Core Facilities Recreation
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C++ for high-performance signal processing is a plus. Experimentation: Proven experience developing wireless prototypes, demonstrators, or proof-of-concept systems. Signal Processing: Solid knowledge
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programming experience is a plus. Programming Skills: Strong experience with MATLAB and/or Python; experience with C++ for high-performance signal processing is a plus. Experimentation: Proven experience
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scientific computing in high-performance computing environments are essential. Excellent written and spoken English skills are required. We are also looking for someone with experience with 3D image processing
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contribute to high-impact research on machine learning related to the analysis of IoT data in the form of multivariate time series. The DESS group is part of Department of Computer Science that belongs