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preferred. Strong data analysis skills and ability in programming languages, such as Python, for performing experiments and analyzing data. Knowledge of innovative phase retrieval algorithms is desirable
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agents for X-ray spectroscopy by integrating large language models (LLMs) with physics-aware spectroscopy workflows. The researcher will work closely with a multidisciplinary team of X-ray physicists and
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strong track record in problem solving and scientific publications. The candidate will be expected to conceive of, plan, and implement the scientific research, and to report relevant results in
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Strong written and oral communication skills Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork Preferred Qualifications Experience with block copolymer patterning
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written and oral communication across all levels of the organization Ability to present research at technical meetings and publish results in peer reviewed journal articles. Ability to model Argonne’s core
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may include work at Jefferson Lab, the Electron-Ion Collider (EIC) program, detector research and development, and applications of AI in nuclear physics. Applications received by Tuesday, November 4
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computer-aided design software. Collaborative skills, including the ability to work well with other divisions, laboratories, and universities. Ability to demonstrate strong written and oral communication
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++, or similar languages. Demonstrated expertise in machine learning, especially in the context of dynamical systems modeled by differential-algebraic equations. Experience with high-performance computing and the
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spectroscopy, as well as experience with high resolution STEM imaging • Excellent written and oral communication skills Job Family Postdoctoral Job Profile Postdoctoral Appointee Worker Type Long-Term (Fixed
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, computational science, a physical science, or engineering or related field. Comprehensive experience programming in one or more programming languages such as Python, C/C++. Experience with one of the AI