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Postdoctoral position in the development of an AI-based phenotyping system for high-throughput sc...
interdisciplinary center for research and education in quantitative genetics and quantitative genomics (http://www.qgg.au.dk/en). QGG is an international organization with 70 employees and visiting researchers from
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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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interdisciplinary center for research and education in quantitative genetics and quantitative genomics (http://www.qgg.au.dk/en). QGG is an international organization with 70 employees and visiting researchers from
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | 3 months ago
deterministic inversion approaches. Low-order arithmetic offers promises of important cost-reduction via the use of GPUs, and is commonly used in learning approaches, it has therefore become a central block of an
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data from the European XFEL facility at DESY. Project website: https://www.mpinat.mpg.de/628848/SM-Ultrafast-XRay-Diffraction Your profile Eligible candidates have strong skills in computational physics
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efficient GPU-supported implementation. Your tasks: Development of physics-aware ML models for 3D blood-flow prediction Integration of domain decomposition methods into the learning framework to enable
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 2 months ago
for the physical characterization of planetary surfaces., in: European Planetary Science Congress. pp. EPSC2024-535. https://doi.org/10.5194/epsc2024-535 Haggstrom, P.L.C. Rodrigues, G. Oudoumanessah, F. Forbes, U
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-following inverters. Implementing and optimizing scalable algorithms for transient and stability analyses on HPC architectures (CPU, GPU, hybrid). Enhancing the numerical robustness and efficiency of existing
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members in designing and integrating solutions into the AI(X) compute, software and data infrastructure stack, hardening these solutions, testing these on modern high-performance GPU compute clusters, and
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regulation to neuronal function and circuits. State-of-the-Art Infrastructure: Access to advanced sequencing, imaging platforms, and high-performance GPU computing. Research Environment: An international