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Field
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optimization technologies are revolutionizing the way power grid is operated and planned. CEEESA is seeking talented and motivated researchers to enhance its capability in solving energy challenges using
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, surrogate modeling of scientific processes, workflow automation and adaptive simulation pipelines, and performance analysis and optimization. The candidate will also contribute to and help originate research
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collaborative environment with projects and interactions spanning multiple labs within the group, across NIST and externally. Candidates should have a PhD in physics, electrical engineering, mechanical
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adaptive optimization during needle insertion, integrating live ultrasound imaging with GPU-accelerated dose calculation and optimization. The Postdoctoral Research Associate will join a multidisciplinary
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motivated Postdoctoral Researcher to join our Grid Planning and Analysis Center (GPAC). This position will focus on tackling critical optimization challenges in medium-term power system planning like
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. Role & Responsibilities: Design and optimize large-scale electrophysiological and behavioral experiments using next generation custom-built hardware and software platforms Develop and implement end
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unique opportunity to engage in transformational research that advances the development of AI-ready scientific data, optimized workflows, and distributed intelligence across the computing continuum. In
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the operations and data analysis of the HAYSTAC experiment, as well as in the commissioning, optimization, and development of analyses for the ALPHA experiment. The candidate is also expected to take a leadership
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research with a strong focus on cardio‑oncology populations. We are seeking a highly motivated postdoctoral dietitian (PhD RD) who is eager to contribute to innovative clinical and behavioral intervention
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refinement of innovative research methodologies and will independently design, optimize, and execute complex immunologic and molecular experiments across in vitro, ex vivo, and in vivo model systems. Technical