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Interaction, or a related field Strong background in scientific visualization, visual analytics, or interactive data exploration Experience programming in one or more languages such as Python, C/C
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physics, etc. Proficiency in Python or other scientific programming languages. Programming skills in numerical methods for image processing and AI/ML methods for quality improvement are advantageous
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programming, interfacing hardware, and developing machine-learning methods highly desirable. The researcher will join an Argonne funded project with interdisciplinary team of material scientists, computer
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Extensive knowledge of Microsoft Excel and good computer programming skills Knowledge of techno-economic analysis and life cycle analysis Experience working with Argonne’s EverBatt model, GREET model, and
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with applying unsupervised ML algorithms such as autoencoders, clustering, to time-series data is preferred Experience with the data from HEP experiments is strongly required Programming expertise in
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interfaces. Programming and HPC: Strong scripting and data analysis skills; experience with high-performance computing environments and job schedulers. Demonstrated ability to work in multidisciplinary teams
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Hands-on experience with two-dimensional materials modeling Proficiency in database development and management for computational materials data Strong programming skills and experience with software
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areas: high-pressure science, synchrotron X-ray techniques, rheology, Raman spectroscopy, and Python programming, among others. Ability to model Argonne’s core values of impact, safety, respect, integrity
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detectors while also having flexibility to pursue your own research interests. Research Focus Participate in a detector R&D program aimed at developing superconducting nanowire sensors to enable
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. Familiarity with total scattering/PDF techniques and related software. Hands-on experience with lasers, timing/synchronization, or detector systems. Scientific programming skills (e.g., Python) for data