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and heterointerfaces. The postdoc will lead experimental design, data acquisition, and quantitative reconstruction. The appointees will work within a highly collaborative team spanning multiple DOE user
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-throughput laboratory systems Proficiency in Python or similar programming languages for data processing, statistical analysis, and integration with AI/ML tools Excellent written and verbal communication
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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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microwave resonator design, characterization, and RF/microwave measurement techniques Electromagnetic simulation experience (e.g., Sonnet, Ansys HFSS/Lumerical, or similar tools) Experience with data
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of cathode operation and degradation, and identify pathways to improve the performance and safety of advanced electrochemical cells Analyze and interpret experimental data and communicate findings through
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will receive full consideration. Key Responsibilities AI-ready data and analysis for the ePIC Barrel Imaging Calorimeter and our Jefferson Lab program Support for the PRad-II and X17 experiments
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cryogenic environments Participate in synchrotron-based characterization and data analysis Contribute to high-impact publications, internal reports, and scientific presentations at conferences and workshops
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work with a multidisciplinary team to advance agentic AI tools for simulation, interpretation, data analysis, and scientific discovery. The appointment is expected to last two years and the contract is
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work within a multidisciplinary team with researchers at MERF and collaborators inside and outside Argonne. The candidate is expected to design and conduct experiments, analyze data and explore
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., Python, Fortran, C++) Knowledge of data analysis techniques and statistical methods Proven scientific writing and oral communication skills Ability to work both independently and collaboratively in a team