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environment. This includes a HPC cluster with NVIDIA H100 nodes, parallel storage and fast interconnects, dedicated workstations with multiple A6000 GPUs, and web-based services via Microsoft Azure
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Engineering, or a related field Strong experience in building and optimizing AI systems using PyTorch, TensorFlow, or JAX Practical knowledge of NVIDIA GPU programming (CUDA) and experience with inference
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transcriptomics. Innovative visualization tools and highly automated analytical pipelines powered by GPU technology. Mentorship from experienced scientists in data analysis and management, with an expertise in
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quantitative genetics, machine learning, bioinformatics, and population genetics, and their applications in an agricultural setting A modern dedicated computational infrastructure (CPUs & GPUs) Well-developed in
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Empire Innovation Professor (Associate Professor) Artificial Intelligence in Biomolecular and Drug D
. This position offers substantial resources, including access to the SeaWulf computing cluster and cutting-edge GPU clusters housed at IACS and CEWIT. The Empire Innovation Professor will join a robust community
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provided with the working material (working station, PC and access to local GPU clusters) as well as with a discounted rate for the close-by Inria canteen, together with a gross salary of 2650 euros/month
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libraries like NCCL/RCCL and experience with high performance computing middleware is highly desirable. Optimizations of large parallel code bases and experience with GPU programming languages such as CUDA