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Field
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to begin September 1, 2025. We will consider strong candidates in any research area but will prioritize Distributed and Parallel Computing. A PhD in computer science or a related area is required
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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 emergence of edge computing, data storage will become more geo-distributed to account for performance or regulatory constraints. One challenge is to maintain an up-to-date view of available content in such a
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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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) and parallel computing, with a focus on cost-efficient and scalable model deployment. Skilled in working with medium-large scale multicore and heterogeneous (CPU + GPU) clusters. Excellent verbal and
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working with high performance computers (e.g., parallelizing and distributing code). Experience in distributed data management and workflow systems. Preferred Competencies Ability to work independently and
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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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for parallel processing of high-performance computing (HiPerGator) and high-performance data analytics workflows together with data scientists. Deploy data infrastructure and systems on standard Linux servers
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insights from related small models, and employ distributed optimisation and parallel computing to investigate knowledge transfer and interaction between small and large models; (b) assist in general
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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