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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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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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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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nature of electroweak symmetry breaking and mass generation in the standard model. We developed state of the art (open source) software working on GPU- and CPU-based supercomputing architectures, and
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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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as code” approach to systems automation. You’ll be working across a range of predominately Linux based systems, including HPC and GPU accelerated compute, large-scale and high-performance storage, and
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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
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of code to utilize GPU-acceleration on DTU’s high-performance computing cluster or other HPC systems. You will also analyze realistic physical implementations of the architectures you explore, with a
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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