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must provide proof of U.S. citizenship, which is required to comply with federal regulations and contract. Skill in devising and performing experiments to acquire identified data, using and maintaining
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50,000 registered users worldwide, including academia, industry, and regulatory agencies. The SAC has been working closely with energy and auto industries, universities, and governmental agencies
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The Applied Materials Division (AMD) at Argonne National Laboratory is seeking to hire a Post-doctoral Researcher. The candidate will work within a multidisciplinary team with researchers
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(typically completed within the last 0-5 years) in material science or related chemistry science with 0 to 1 year of post-graduate experience. Knowledge in the areas of materials science, metallurgical and
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, which is required to comply with federal regulations and contract. Work conducted under this posting will require the appointee to obtain a security clearance. This level of knowledge is typically
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in spatial analysis and data visualization Computer programming skills relevant for data manipulation and analysis Experience with creating and using complex data-driven analytical models using R
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
: Expertise in rare event simulation, deep learning, and developing computationally efficient approaches for simulation and modeling in complex systems is highly desirable Experience with parallel computing
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electrochemistry. Position Requirements Skill in devising and performing experiments to acquire data; using and maintaining research equipment; compiling, evaluating, and reporting test results. Experience in
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such we are looking for a candidate that has shown the ability to create their own experimental apparatus to solve challenges. The position will require flexibility and a willingness to learn new
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Applications are invited for post-doctoral positions in the Cosmological Physics and Advanced Computing Group (CPAC) Group in Argonne National Lab. Research at CPAC covers theory, modeling