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Field
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maintenance of a viable research program. The candidate's research program should contribute to the areas of parallel scientific computing, with experience in several of the following areas: mesh generation
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SLICES-FR research infrastructure- Communicate results through presentations, conference papers, and project reportsProfile and skillsThe R&D Engineer must already hold a PhD degree in Computer
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the forefront of RNA biology, utilizing massively parallel reporters to identify sequence and structural elements that regulate mRNA stability and translation. In this role, the candidate will leverage
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with an emphasis on translational application and therapeutic development. The Cornea Biology Laboratory, under the direction of Sophie Deng, MD, PhD, studies corneal stem cells aiming to develop novel
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PhD degree in Computer Science, Physics or a related field Experience with parallel programming models Strong programming skills in C/C++ and/or Python Knowledge of distributed memory programming with
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of biology and the effect of mutations. He/she would also be required to have a sound computational background, especially in the area of simulations. Criteria of the candidate: PhD in the field
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extensive cell tracking studies with massive parallel sequencing and molecular manipulations to gain insights into regulatory mechanisms whose appropriate targeting could impose regenerative traits to mammals
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-economic environment in Morocco and Africa. HTMR provides highly automated and parallel approaches to the development of new materials and processes. HTMR allows scientists from all UM6P research community
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Post-doctorate position (M/F) : Exascale Port of a 3D Sparse PIC Simulation Code for Plasma Modeling
, C. (2023). Approche sur grilles parcimonieuses pour accélérer la méthode PIC (PhD, Toulouse 3). - Participate in the Exascale porting of 3D sparse-PIC code, including distributed parallelism
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Identify new applications for Machine Learning in science, engineering, and technology Develop, implement and refine ML techniques Implement parallel ML training on the High Performance Computers Engage in