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communicate effectively with the team to debug the model. The OLG model codebase is technically challenging and computationally demanding. For example, it solves dynamic programming problems with GPU
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techniques. Preferred Qualifications: Knowledge of HPC matrix, tensor and graph algorithms. Knowledge of GPU CUDA and HIP programming Knowledge on distributed algorithms using MPI and other frameworks such as
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University of California, Los Angeles | Los Angeles, California | United States | about 2 months ago
management of a state-of-the-art medical imaging research data center. The environment includes a robust multi-CPU/GPU architecture with virtual and physical servers, supporting advanced parallel computation
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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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learning for policy optimisation, all within a huge GPU-based simulation with thousands of robots learning synchronously in parallel. The best solutions will then be 3D-printed, and policies will be fine
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needs, such as assisting the team with evaluating evolutionary algorithms for exploring creative new hand designs, or reinforcement learning for policy optimisation, all within a huge GPU-based simulation
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Supercomputer Center which houses a 20 PFLOP CPU+GPU-capable machine. Application Requirements Document requirements Curriculum Vitae - Your most recently updated C.V. Cover Letter (Optional) Statement of
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is also the home of the Vermont Advanced Computing Center, a research facility with both high-performance CPU and GPU clusters. The Larner College of Medicine is a short (<5 minutes) walk from
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is also the home of the Vermont Advanced Computing Center, a research facility with both high-performance CPU and GPU clusters. The Larner College of Medicine is a short (<5 minutes) walk from
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of machine learning models Preferred skills/knowledge includes: A Master’s degree Training and optimizing ML algorithms on GPU hardware architectures, specifically NVIDIA based Working with geo-spatial data