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studies (e.g., EELS, EDS) to probe defect structures and dynamics Apply advanced image processing and analysis; develop AI/ML workflows for quantitative defect characterization Implement high-throughput and
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or image processing Experience with AI-assisted or feedback-driven fabrication workflows Interest in quantum photonic platforms, electro-optic systems, or light–matter coupling physics Application Materials
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. Education: Ph.D. (< 5 yrs. since Ph.D.) • Familiarity with image processing and simulation software. • (Preferred) Experience with nanofabrication, transport measurements, thin film deposition, in-situ TEM
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synchrotron-based techniques to inform process development. The role requires a strong background in synchrotron characterization techniques, mainly three-dimensional imaging (microtomography and
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Science and Engineering, Environmental Engineering, or a related field with 0 to 2 years of experience. Demonstrated understanding of membrane separation processes and principles. Hands-on experience in
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The Chemical Sciences and Engineering Division invites you to apply to a postdoctoral appointee opening. The successful candidate will perform research in the Interfacial Processes Group
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and processing strategies aimed at achieving high performance, cost-effectiveness, and manufacturability. The selected candidate will leverage the capabilities of the Materials Engineering Research
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such as PyTorch and TensorFlow. Experience with high-performance computing and/or scientific workflow. Strong background in inverse problems, numerical optimization and image processing. Job Family
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engineering team to translate the models into production. The successful candidate will be part of a cross-lab, highly inter-disciplinary team of experts in ML, applied math, HPC, signal processing