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physical characterization techniques (differential scanning calorimetry, dynamic light scattering, small angle neutron and/or x-ray scattering) to characterize the DIBs; and (3) Develop/implement image
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computational models for quantum magnets and neutron scattering observables. Generate, document, and manage synthetic datasets (e.g. S(Q,ω), diffraction, thermodynamic data) for AI training and validation
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, pyrometry, spectroscopy, co-axial and off-axis high speed imaging, and more) for process monitoring and diagnostics. Develop and implement data acquisition, signal processing, and data analytics frameworks
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computed tomography (CT) reconstruction, including sparse-view and limited-angle algorithms, and the application of advanced machine learning (ML) and computational imaging methods to scientific and
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, fusion, materials, life sciences, and other strategic domains. Investigate novel approaches for balancing efficient I/O, interoperability, and scientific validity in AI-ready datasets. Design, prototype
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thermal analysis (DSC/TGA). Hands-on experience in materials characterization using tools such as particle size analysis, optical microscope, scanning electron microscopy, X-ray diffraction. Strong
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-resolution microscopy, and in situ neutron or X-ray scattering and tomography methods. Strong background in computational and image-processing software, scientific programming, and high-performance computing
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, the Frontier supercomputer, and collaborate with experts in machine learning, optimization, electric grid analytics, and image science. The successful candidate will design and implement differential privacy
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). NCCS operates the Frontier exascale supercomputer and world-class data facilities. This role sits at the intersection of AI at scale and HPC, giving you unmatched resources to prototype new ideas, run