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, energy systems, computational engineering, or a related field Strong background in numerical methods, mathematical modeling, and network simulation or analysis Good understanding of power systems, gas
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analysis, based on particle-in-cell (PIC) simulations, in order to (1) compare the effect of different types of broadband sources on the growth and saturation of three-wave coupling instabilities (Raman and
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1 Aug 2026 Job Information Organisation/Company CNRS Department Laboratoire d'analyse et d'architecture des systèmes Research Field Mathematics History » History of science Researcher Profile First
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research; You will present your work at international conferences for academics, policy makers, and educators. Where to apply Website https://www.academictransfer.com/en/jobs/362930/phd-a-multimodal-analysis
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activity of individual neurons and mesoscopic population signals. His team develops open software for analysis and data management that forms the technical basis of the proposed project. The PhD candidate
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physics or other relevant fields. Prioir experience in cleanroom processing and/or thermal or material analysis is highly recommended. TU Delft (Delft University of Technology) Working at TU Delft means
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should demonstrate: Strong mathematical, analytical, and problem-solving skills. A solid foundation in engineering principles and quantitative analysis. The ability to work independently and as part of a
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Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. | Dortmund, Nordrhein Westfalen | Germany | 3 months ago
for the AMBIOM (Analysis of Microscopic BIOMedical images) Research Group: PhD Candidate (m/f/d) You will be responsible for Developing large-scale microscopy image analysis pipeline for 3D microscopy images
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5 Jul 2026 Job Information Organisation/Company CNRS Department Laboratoire d'analyse et d'architecture des systèmes Research Field Mathematics History » History of science Researcher Profile First
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Health Data Sciences and Informatics (OHDSI, https://ohdsi-europe.org ) initiative, dedicated to bring out the full value of observational health data through the OMOP Common Data Model and large-scale