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for the turbomachinery design optimization process conducted by a parallel PhD student at LMFA. The numerical solver involved is ProLB. It is an innovative Computational Fluid Dynamics (CFD) software solution developed
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details, the following tasks will be carried out in parallel: 1. The PhD student will extend the current database (see, J. Chem. Theory Comput.2025, 21, 8010−8033) by obtaining highly-accurate reference
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) Positions PhD Positions Application Deadline 1 Jun 2026 - 00:00 (Europe/Paris) Country France Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The deposition of polymer brushes on solid surfaces creates versatile
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Application Deadline 23 Mar 2026 - 23:59 (Europe/Paris) Country France Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | about 2 months ago
-09731 Requirements Skills/Qualifications Candidate profile - Master degree Computer Sciences. - Experience in scientific programming (e.g., Python, C++, Fortran, Julia) and parallelization
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, Interactive and Cognitive Systems, Distributed Systems, Parallel Computing, and Networks. The host team, DAISY, is a joint CNRS, Grenoble INP, and UGA research team handling research challenges
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Offer Starting Date 1 Sep 2026 Is the job funded through the EU Research Framework Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description
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Starting Date 1 May 2026 Is 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
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through sensitivity, uncertainty, and scalability analyses. – Enhance the computational efficiency of large-scale optimization problems by exploring decomposition techniques, parallelization, and