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. Demonstrated experience developing and running computational tools for high-performance computing environment, including distributed parallelism for GPUs. Demonstrated experience in common scientific programming
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with the use of laminar/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
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. Correlate fluorescence, label-free, mass spectroscopy, and microscopy data form a microarray platform to develop a parallel readout of protein function. Correlate and curate data from various instruments and
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research resource for the department, ensuring reliable study execution and operational support for faculty research. In parallel, the postdoc will advance their own research program and collaborate with
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 3 hours ago
interprofessional education to ensure a highly skilled workforce. Research: We develop and support a rich array of outstanding health sciences research programs, centers and resources. We provide infrastructure and
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system. We have a variety of ongoing projects that leverage high throughput reporter assays (e.g., Massively Parallel Reporter Assays) to understand gene regulation in the living brain. We apply
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their own research program in collaboration with, and in parallel to, Prof. Zanazzi. Penn State hosts a vibrant community of scientists working on many aspects of exoplanetary astrophysics, including
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of computer science fundamentals including algorithms, data structures, and object-oriented programming. Proficiency in C/C++ or similar language Working with large codebases Containerization (Docker) and building
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applications. You’ll help design, train, and evaluate AI systems that plan, reason, and take actions to accelerate scientific discovery across domains (materials, chemistry, climate, fusion, biology, and more
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programming distributed systems; Experience with parallel and distributed File Systems (e.g., Lustre, GPFS, Ceph) development. Advanced experience with high-performance computing and/or large-scale data centers