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-completed PhD (within the last 0–5 years) with strong background in physical chemistry, photophysics, photochemistry, and polariton chemistry Hands-on experience in thin-film deposition, and spectroscopic
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formal education in chemical engineering, chemistry, materials science, nuclear engineering, mechanical engineering, or related field at the PhD degree level with zero to five years of experience
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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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The Mathematics and Computer Science Division (MCS) at Argonne National Laboratory is seeking a Postdoctoral Appointee to conduct cutting-edge research in scientific machine learning, focusing
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instrument proposed under a DOE Major Item of Equipment (MIE) effort. Building on two decades of APS XRS capability (including the LERIX program at 20-ID) and recent commissioning work at Sector 25
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methodologies and tools for economic and ecological analyses of hydropower systems. The position will involve the development and use of computer models, simulations, algorithms, databases, economic models, and
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in materials for electrochemistry. While the focus in on computational expertise, this position will involve some experimental work in adapting workflows for automation and artificial intelligence
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multidisciplinary team, the candidate will work at the intersection of AI/ML, domain sciences, and high-performance computing. The role requires a strong foundation in LLMs and machine learning, along with
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collaboration with team members. Skilled written and verbal communicator, including the ability to present complex information so that it is understandable to a broad audience. Computer skills relevant for data
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, materials synthesis, and separation processes. Position Requirements Recent or soon-to-be-completed PhD (typically within the last 0–5 years) in chemistry, geochemistry, chemical engineering, physics