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). The selected candidate will support modernization efforts by: Developing FPGA designs based on the MicroTCA platform for applications ranging from distributed timing synchronization, low latency fault protection
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that accelerate AI/ML when applied to large scientific data sets; Energy efficient physics-aware algorithms, capable of distributed learning on high performance and edge computing; The design of architectures
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experimental facilities. You will be responsible for developing energy-efficient, physics-aware algorithms designed for distributed learning across both high-performance and edge computing environments. You will
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statement from the Lab Director’s office can be found here: https://www.ornl.gov/content/research-integrity Basic Qualifications: PhD in physics, computer science, engineering, or a related field with at