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We are seeking a highly motivated Postdoctoral Appointee with a strong background in artificial intelligence and machine learning (AI/ML), with particular emphasis on the development and application
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to study chemical transformations in materials. 2. Artificial Intelligence Applications: - Leveraging conventional machine learning techniques for materials property prediction and Bayesian approaches
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autonomous experimental campaigns, this position is suited for a highly energetic and self-driven researcher willing to work in highly collaborative teams. This position will involve a considerable amount of
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beyond the Standard Model, including effective field theories and perturbative QCD, phenomenology at current and future colliders, as well as emerging areas in Artificial Intelligence, Machine Learning
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, machine learning, and control in the energy sector. The postdoc researcher will perform theoretical study and algorithm development on optimization/control/data analytics methods and authorize peer-reviewed
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clustering, redshift-space distortions, weak/strong gravitational lensing, and artificial intelligence/machine learning (AI/ML). The observational focus is on optical sky surveys (DES, DESI, Roman, Rubin Obs
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
: Expertise in rare event simulation, deep learning, and developing computationally efficient approaches for simulation and modeling in complex systems is highly desirable Experience with parallel computing
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. Additionally, the CPS provides an interdisciplinary home for spawning simulation programs and projects, often in collaboration with the ALCF. The ALCF and CPS division are seeking a postdoctoral appointee to
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, datasets, and risk monitoring tools in collaboration with DOE national laboratories and federal partners. Prepare detailed reports and briefings on methodologies, analyses, and findings. Collaborate with
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collaborating with a software engineering team to translate research into production-ready tools. The successful candidate will be part of an inter-lab, highly inter-disciplinary team of experts in ML, applied