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Field
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programming; Experience programming distributed systems; Experience with parallel and distributed File Systems (e.g., Lustre, GPFS, Ceph) development. Advanced experience with high-performance computing and/or
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groups settings. Ability to coordinate with faculty, graduate and undergraduate students, and external collaborators. Skills in parallel computing, parallel application design and development, and
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programs for work management, retrieve workflow information, job assignments and material and labor data entry. Must be accurate and timely in the use of the Computerized Maintenance Management System (CMMS
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to statistics and data science, behavioral economics to social and political history, Dietrich College is home to 11 humanities and sciences departments, programs and institutes. Our world-class faculty and
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. Proficiency in Python programming and major ML/DL frameworks (e.g., PyTorch, TensorFlow). Solid understanding of optimization and regularization methods for training complex neural networks. Practical knowledge
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settings. Specific Duties & Responsibilities 70% Systems Engineering, Administration, Security, and Oversight Work with Sr staff to design, organize, plan, test and implement cutting-edge hardware designs
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/neuropixel probes and electrical microstimulation to study attention and decision making networks in a behaving animal model together with parallel studies in humans. The project is part of a NIMH Silvio O
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. In parallel, the Deng team is conducting the preclinical studies on developing extracellular vesicles to treat corneal scarring. Both research programs are funded by the National Eye Institute and
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Mathematics, or a related field, awarded within the last five years Programming experience in one or more of Python, C++, Fortran, or Julia Knowledge of high-performance and parallel computing Experience
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sequence programming (e.g., IDEA/ICE) and contemporary image reconstruction techniques (e.g., compressed sensing, parallel imaging, model-based or deep learning reconstructions). Knowledge of radial data