860 data-"https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" positions in Denmark
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grant from the European Research Council. The primary challenge in powering AI chips and future data center systems is enhancing the efficiency of voltage regulator modules (VRMs) to meet their
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and transport systems, within the ELLIS network. The project is fully funded through the Novo Nordisk Foundation Data Science Distinguished Investigator programme. You will be based in the Intelligent
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sets, lexicon development, use of instrumental techniques to correlate or predict sensory characteristics and multivariate data analysis. This position is part of an interdisciplinary research project
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activities in the SDU Robotics project activities. For a research project in the field of lab automation we are looking for a student assistant: Robotic and mechanical focused: Helping with data analysis and
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underlying greenhouse gas fluxes Support training of young researchers in using biogeochemical observations and data analysis Write and contribute to international peer-reviewed publications Contribute
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). Incorporate realistic WGS data analysis, antimicrobial susceptibility testing, and epidemiological trace-back into interactive scenarios. Create scoring systems, feedback mechanisms, and learning outcomes
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chemistry parameters, sediment and soil nutrients (especially carbon and phosphorus), and measurements of greenhouse gas dynamics. Experience in handling and analyzing large and continuous data sets covering
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. In Viborg the place of work is Blichers Allé 20, 8830 Tjele. The area of employment is Aarhus University with affiliated institutions. Contact information For further information, please contact
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paths at DTU here . Further information Further information may be obtained from Professor Xenofon Fafoutis and Associate Professor Luca Pezzarossa . You can read more about ESE at www.compute.dtu.dk
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join us. At DTU Chemical and Biochemical Engineering, you will operate at the forefront of computational modelling, integrating high‑fidelity CFD with advanced compartment models and modern data‑driven