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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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four staff members [Ian Cloët, Alessandro Lovato, Anna McCoy, and Yong Zhao] and several postdocs and students. The group has a broad research program in QCD/hadron physics and nuclear structure
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computational research. They are intrinsically driven, goal-oriented, and can work collaboratively with others. Working closely with the CPS divison, the postdoc will leverage AMReX and the LBM to develop
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, presentations, software, datasets, and internal reports Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in chemistry, chemical engineering, materials science, polymer science
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-friendly software interfaces that enhance data accessibility of data and insight for diverse stakeholders. Facilitate ongoing communications and foster relationships with a broad array of stakeholders
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measuring MEMS devices, as well as designing feedback loops and control algorithms for their precise operation Experience using software tools to simulate the physical properties and behavior of MEMS
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deep learning including data collection, architecture development, model training, and validation Interest in software development, with particular emphasis on the Python programming language and
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devices, with emphasis on lithium-ion, sodium-ion, and lead-acid battery systems. Modeling and analysis will leverage tools such as COMSOL, MATLAB, Excel, Python, and related scientific software. The role
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sensing, quantum information science, superconducting circuit, or magnonics. Proficiency in scientific software development (e.g., Python, COMSOL, HFSS or similar languages). Ability to model Argonne’s core
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, heterogeneous datasets and developing reproducible analytical workflows, including using LLMs for the same. Demonstrated software development practices, including documentation and version control. Skilled in