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Temporary Job Status Part-time Hours Per Week 5 Offer Starting Date 1 Jun 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number PN-IV-P7-7.1-PTE
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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 At the Futuroscope site
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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 At the Futuroscope site
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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 At the Futuroscope site
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23 Mar 2026 Job Information Organisation/Company PHAETHON Centre of Excellence Research Field Engineering » Mechanical engineering Engineering » Electrical engineering Computer science Mathematics
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scientific documents Degree, training and accreditation Degree : doctorate or PhD Field of study : Computational Mechanics LanguagesENGLISHLevelGood Additional Information Work Location(s) Number of offers
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the coupled dynamics of roots, mycorrhizal fungi and soil resources under varying environmental conditions. The work will integrate concepts from applied mathematics, computational mechanics and biological
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! Education · PhD in computer science, engineering, applied mathematics, physics, or another STEM discipline. · Demonstrated experience with mathematical and numerical optimization methods
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the job 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 Scientific field and
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Research Assistant (m/f/d) with a Ph.D. in Civil Engineering, Engineering Physics, Physics, Mathemat
predictions for digital‑twin applications. Your responsibilities include: Development and implementation of thermo‑mechanical models in FEniCSx Integration of FEM models into neural operators and PINNs