51 programming "https:" "https:" "https:" "https:" "https:" "Data driven Materials Modeling" positions at Argonne
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on understanding novel and emergent behavior in nanoscale magnetic heterostructures, particularly in confined 2D van der Waals magnets and related devices. The goal of the program is to study and control magnetic
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of multi-omic data Programming Proficiency: Strong knowledge of Python, C/C++, Julia, and other relevant programming languages Ability to model Argonne's core values of impact, safety, respect, integrity
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engineering, or a related field. Strong programming skills in Python and experience developing research or production-quality machine learning software. Experience with machine learning or deep learning
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interactions, or aerosol–cloud interactions Strong experience in numerical modeling and high-performance computing • Experience applying AI/ML methods to model development, with strong programming skills (e.g
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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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physics. Familiarity with scientific programing languages such as python. Job Family Postdoctoral Job Profile Postdoctoral Appointee Worker Type Long-Term (Fixed Term) Time Type Full time The expected
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Plan and execute in situ/operando experiments using advanced characterization methods, including Near Ambient Pressure X-ray Photoelectron Spectroscopy (NAP-XPS), electron microscopy, Raman spectroscopy
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among material properties, electrochemical performance, and battery system cost at the material, cell, and pack levels. The researcher will plan and advance performance and cost modeling of energy storage
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, ptychography, Laue microdiffraction, or related coherent/imaging techniques. Proven ability to design, conduct, and analyze complex synchrotron experiments. Proficiency in scientific programming (Python, MATLAB
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using Python, MATLAB, or equivalent programming languages. Preferred Qualifications • Working knowledge of X-ray optics, detector systems, and beamline instrumentation. • Background knowledge in ultrafast