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frameworks (e.g. PyTorch, TensorFlow) and relevant libraries. Practical experience in scalable data processing, including the use of parallel computing, cloud platforms, and distributed systems for efficient
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, copyrighted, or biased. By studying brain data recordings and building computational models that mimic real populations of neurons, the project aims to uncover active unlearning: how the brain learns
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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 14-May-25 Location: Philadelphia, Pennsylvania Type: Full-time Categories: Academic/Faculty Computer/Information
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You will be working in a larger research and development project in parallel, distributed and heterogeneous computing. The project work can, under certain circumstances, be combined with an internal
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the management of national and campus-level high-performance computing (HPC) clusters and their associated storage systems, including large parallel file systems, NFS file servers, and underlying storage
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PhD degree in Computer Science, Physics or a related field Experience with parallel programming models Strong programming skills in C/C++ and/or Python Knowledge of distributed memory programming with
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simulation, AI based detector design optimization, streaming computing model development, production, distributed computing and workflow management, software infrastructure, particle ID, tracking
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welcome applications from all areas of computer science, we especially encourage candidates with expertise in: Software Engineering Cybersecurity Artificial Intelligence and related domains Parallel and
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departmental website (Drupal.) 4. Support discipline specific software applications (AutoCAD, Powermill, distributed computing management, Rhino, Maya, Maxwell, and Revit); in addition, provide support for Yale
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. Documents requirements, defines scope and objectives, and formulates systems to parallel overall business strategies. Responsibilities Job Responsibilities: 1. Assists with program planning and implementation