77 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at Argonne
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reinforcement learning Experience with high-performance computing, physics-based simulations, and multimodal data workflows Demonstrated ability to train and deploy AI/ML models using simulated and experimental
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familiarity in machine learning (ML) and artificial intelligence (AI). This role is pivotal in evaluating the economic competitiveness of the U.S. in the production and manufacturing of energy-related materials
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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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physics (HEP) and nuclear physics (NP) experiments. The successful candidate will be a key member of a multidisciplinary co-design team integrating materials science, computing, and device engineering to
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to the Lab’s broader effort in CH4 and CO2 utilization R&D. The role will require the individual to work with personnel that perform machine learning and molecular simulations and electrochemical device testing
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”, “Firstname_Lastname_cover_letter”. Include links to code examples in your CV (e.g., GitHub page, past project repositories). Position Requirements A recent PhD (completed within 5 years, or soon to be completed) in computer
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The Cosmological Physics and Advanced Computing (CPAC) group at Argonne National Laboratory invites applications for a postdoctoral researcher to work closely with Dr. Lindsey Bleem
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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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samples and characterize dynamic behaviors. The candidate will be part of a highly collaborative team and actively interact with other groups, including optics, computation, and time-resolved research
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at technical conferences. Position Requirements Recent or soon-to-be-completed PhD (typically completed within the last 0-5 years) in mechanical engineering, materials science, civil engineering, computer