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genes in plants, and modeling the evolution of transcriptional systems in silico . We are currently looking for a talented postdoc to join our team in the context of a project funded by the Research
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of the Candidate: Completed a PhD in engineering, applied physics, applied mathematics, or a related field. Strong quantitative skills and modeling Advanced coding skills Fluent (oral and writing) in English Enjoys
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plants, and modeling the evolution of transcriptional systems in silico. We are currently looking for a talented postdoc to join our team in the context of a project funded by the Research Foundation
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University (ASU) invites applications for two postdoctoral scholar positions in the area of mathematical modeling to work with Dr. Nina Fefferman. The first position will focus on modeling dynamics
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Start date: September 2026 (flexible) Duration: 3 years (36 months) Project The High Performance Computing (HPC) research group (Prof. Florina M. Ciorba), Department of Mathematics and Computer
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Applications are invited for the position of Research Associate in the Department of Pure Mathematics and Mathematical Statistics. The successful applicant will join the ERC-funded team of Prof
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Disease Dynamics and Interventions group , the role focuses on developing and applying sophisticated mathematical, statistical and computational models to inform vaccination strategies for endemic
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Mathematics, particularly in research areas such as Applied Analysis/Computational Mathematics/Mathematical Modeling/Probability and Statistics, along with excellent professional and research experience; and 3
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18 Mar 2026 Job Information Organisation/Company CYU Cergy Paris Université Department 95300 Research Field Mathematics » Mathematical analysis Researcher Profile Recognised Researcher (R2
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Max Planck Institute for Solar System Research, Göttingen | Gottingen, Niedersachsen | Germany | 8 days ago
of meteorites as well as numerical modeling on state-of-the-art supercomputers. We invite applications for a Postdoctoral Position (m/f/d) in machine learning for PDEs and turbulence control. Machine learning