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-aware learning methods with domain decomposition techniques, enabling parallel training and efficient GPU-supported implementation. Your tasks: Development of physics-aware ML models for 3D blood-flow
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-wave and multimessenger signals and to explore challenging regimes of parameter space. Unit URL https://www.uidaho.edu/science/academics/physics Position Qualifications Required Experience Demonstrated
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diverse scientific domains, pushing the boundaries of AI to solve some of the most pressing scientific challenges. With access to competitive computational resources, we offer an exciting multidisciplinary
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physics, mathematics or any related field. What we offer State of the art on-site high performance/GPU compute facilities Competitive research in an inspiring, world-class environment A wide range of offers
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Postdoctoral position in the development of an AI-based phenotyping system for high-throughput sc...
balance Training and international experience in public–private partnerships Mentoring for career development Access to high-performance computational resources (with GPUs) A collaborative environment
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balance Training and international experience in public–private partnerships Mentoring for career development Access to high-performance computational resources (with GPUs) A collaborative environment
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made at the Postdoctoral Research Associate rank. The AI Postdoctoral Research Fellow will have access to the AI Lab GPU cluster (300 H100s). Candidates should have recently received or be about to
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | 3 months ago
into the high-performance code hawen (https://ffaucher.gitlab.io/hawen-website/ ) with the support of the development team, enabling their application to real-world applications. The program will be divided
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-modal”) neural + behavioral disease-state models. The purpose of the research project(s) this position supports: The purpose of the research supported by this position is to develop a computational
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
the Planetary Surfaces Data and Services Center (PDSSP). In terms of computation, we will strongly rely on the GRICAD computing infrastructure (CPU, GPU, and high performance storage). LanguagesFRENCHLevelBasic