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, design of experiments, image and data processing. Position Requirements Recent or soon-to-be-completed PhD with strong background in Physics or Materials Science (within the last 5 years) Physics
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monitoring and gradient tests. Participate in training opportunities, including attending the US Particle Accelerator School (USPAS). Position Requirements PhD completed in the past 5 years or soon to complete
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models Disseminate research through publications, presentations, and open-source contribution Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in Materials Science, Data
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. The successful candidate will work in the Data Science and Learning division of the Computing, Environment, and Life Sciences directorate of Argonne National Laboratories. Primary responsibilities will be
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with this group to evaluate AERIS at S2S scales, couple ocean component to the model, data assimilation and regional refinement. In particular, this position will utilize generative AI to create a
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-completed PhD (within the last 0-5 years) in field of physics, engineering, or a closely related field Demonstrated programming proficiency in C/C++, Python, or another scientific programming language
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computational scientists to advance a next-generation, user-friendly, agentic AI platform for automated data analysis, interpretation, and user interactions. The appointment is expected to last two years and the
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or soon-to-be-completed PhD (typically completed within the last 0-5 years) in physics, chemistry, or materials science with 0 to 2 years of experience, or the equivalent experience through practical
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Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in physics or a closely related field Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork
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, experience in scaleup is a plus. Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in chemistry and/or closely related discipline. Expertise in the study