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computing and network infrastructure. Ongoing upgrade projects include replacing legacy VME solutions with MicroTCA as well as developing next generation Accelerator Timing and Machine Protection Systems (MPS
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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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that advances the development of AI-ready scientific data, optimized workflows, and distributed intelligence across the computing continuum. In this role, you will have the opportunity to lead and contribute
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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