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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 10 days ago
. These simulations are run on highly parallel supercomputers on which both the hardware and the software are optimized for the task at hand. While the computing power of each processing unit is still increasing, the
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Application deadline: 31/01/2026 Research theme: Control Engineering, Robotics UK only This 3.5-year PhD studentship is open to Home (UK) applicants. The successful candidate will receive an annual
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LevelPhD or equivalent Skills/Qualifications Who you are You have a PhD, preferable in Computer Science, Engineering, Mathematics, or equivalent. You have a strong background with parallel and distributed
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simulation runtimes. During the PhD programme, a student would be expected to explore and analyse the limitations of possible solutions for parallel simulation of massively multicore computers. During
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We are looking for a highly motivated candidate to pursue a PhD programme titled "CFD-informed finite element analysis for thermal control in wire-arc directed energy deposition." This research
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23 Feb 2026 Job Information Organisation/Company Centrale Lille Institut Department North Research Field Engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions
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SPEAR Centre: PhD in ‘Long-Range, High Bandwidth Distributed Acoustic Sensing for Fibre Optic Links’
Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description SPEAR Centre: PhD in ‘Long-Range, High Bandwidth Distributed Acoustic Sensing
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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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distributed computing for EMT simulations. • Experience with software development in Python, C++, or other programming languages. • Familiarity with GPU acceleration of numerical solvers, parallel sparse
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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