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, and progression outcomes) and high-end compute (hundreds of NVIDIA H100 GPUs) via Mila and the Digital Research Alliance of Canada, and involves active collaborations with Stanford, Oxford, Google
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including code design, documentation and testing. Familiarity with optimization methods including Machine Learning (ML) techniques. Any experience with computations on GPUs. Working knowledge of Linux command
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reasoning or tool-augmented LLMs, RL (RLHF/RLAIF/online RL), or foundation models for science, Software engineering skills (Python) and experience with modern DL stacks (PyTorch) and multi-GPU training
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with GPU-accelerated computation and high-dimensional data analysis. Enthusiasm for applying AI innovations to real biological and medical challenges. Required Application Materials: Cover letter
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Preferred Qualifications: Experience in thermos-fluids in porous media. Experience in High-Performance Computing (HPC) on CPU or GPU platforms. Experience in mentoring of graduate and undergraduate students.
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 16 days ago
of data scientists/clinicians and working with unique datasets from multiple academic medical centers (e.g. UNC, UCSF, Mayo Clinic, Memorial Sloan Kettering, etc). Lab dedicated GPU workstations/servers and
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conferences. Qualifications: PhD in computer science with file systems, GPU architecture experience. Proven ability to articulate research work and findings in peer-reviewed proceedings. Knowledge of systems
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for prototyping. Interest and affinity for high-performance computing are necessary for the position. You should have experience with the roofline model and familiarity with a profiler . Experience with GPUs is a