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of Chemical and Biological Engineering Posting Number R260133 Posting Link https://www.ubjobs.buffalo.edu/postings/64055 Employer Research Foundation Position Type RF Professional Job Type Full-Time Appointment
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University of California, Los Angeles | Los Angeles, California | United States | about 17 hours ago
Nextflow or Snakemake, version control such as Git, and reproducible computational environments is preferred. Familiarity with GPU-accelerated genomics, high-performance computing, or cloud-based analysis
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with AMD MI300A GPU+CPU. 2. Perform benchmarking studies to enhance scalability and achieve high node-level efficiency, surpassing existing AMR frameworks. 3. Contribute to communication optimizations
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, validation, calibration, and inference. Working with large, longitudinal, structured and unstructured datasets in Linux and high-performance or GPU-accelerated computing environments. Applying rigorous methods
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and hundreds million) Skills in AI-enabled and GPU-based calculations are welcome Good communication skills and the ability to work in a team environment Ability to work independently to solve critical
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machine learning frameworks (e.g., TensorFlow, PyTorch). Practical experience with cloud computing platforms (e.g., AWS, GCP, Azure). Additional Qualifications: Experience with multi-GPU model training and
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: Psychiatry Group or Departmental Website: https://stai.stanford.edu(link is external) https://neuroailab.stanford.edu/(link is external) https://neuroscience.stanford.edu/(link is external) Does this position
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working on the LHCb experiment at the Large Hadron Collider. The successful candidate will focus on developing LHCb’s real-time data analysis systems, including the GPU-based software trigger. This work
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field theory, semi-classical methods in quantum many body dynamics, tensor networks and GPU-accelerated quantum evolution. Our work is concept- rather than method-centric. Candidates with backgrounds
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transfer (CHT) or fluidic manifold optimization Experience with machine learning/AI (PyTorch or TensorFlow), reduced-order modeling (ROM), or data assimilation (DA) Experience with GPU programming (CUDA and