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model classifiers (PLS-DA, random forest, neural network, etc) towards unraveling materials structure-function relationships, and are familiar with optimization approaches such as genetic search, Bayesian
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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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key element of the two-beam acceleration concept Emphasize Bayesian optimization approaches and integrate these methods into the facility control system Design, execute, and analyze accelerator
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innovative therapeutic strategies for targeting IDPs, including biologics such as protein-protein inhibitors, Proteolysis-targeting chimeras (PROTACs), nanobodies, and more. Key Responsibilities: Develop
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current sensors) Develop and characterize superconducting nanowire single-photon detectors (SNSPDs) using high kinetic inductance materials such as NbN, TiN, and NbTiN, targeting high detection efficiency
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computational science expertise. The ALCF has an opening for a postdoctoral position in data management targeting AI applications at scale. The successful candidate will join the AL/ML group, a vibrant
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. Cosmological research within CPAC covers theory, modeling, observations, and experiments targeted at dark energy, dark matter, primordial fluctuations, inflation, and neutrinos. Theory and modeling activities