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position within a Research Infrastructure? No Offer Description The position targets the design and evaluation of novel architectures, programming paradigms, and parallel algorithms for AI accelerators
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scales through component-based parallelism. The focus of the post-doc position is to design and implement this pipeline -- developing native reasoning for rich combinatorial constraints, creating tools
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transfer, turbulence modeling, and reaction kinetics. Experience with high-performance computing (MPI, parallel simulations) is highly desirable. Demonstrated ability to work independently and
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 33 minutes ago
. The use case is a electrical substation implementing a process bus architecture conformal with IEC 61850 specifications. This includes redundant PRP (Parallel Reduncdancy Protocol) network architectures
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algorithm development and application. Familiarity with common scientific programming languages such as C++. Experience in parallel programming with one or more common parallel programming models, like MPI
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properties (including structural, defect, electronic, ion transport, surfaces) and will link up with parallel experimental activities. Applicants should have a PhD in chemistry, physics or materials science
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Theoretical Physics or a related discipline completed within the last 5 years. Experience with High Performance Computing and programming for massively parallel computers. Experience with quantum many-body
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- and neuron-targeting anti-obesity drugs in these ex vivo systems. In parallel, you will collaborate with a team of postdocs, PhD students, and technicians working with genetic animal models
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framework (e.g., OpenFOAM, ANSYS Fluent). Solid understanding of heat and mass transfer, turbulence modeling, and reaction kinetics. Experience with high-performance computing (MPI, parallel simulations) is
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, mechanical and durability testing, and integration with advanced machine learning models. The postdoc will collaborate closely with CEBE’s parallel work packages. Experimental and analytical data generated in