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of these systems are insufficient to cover the diversity of human-driven experimental activities. The development of multi-appendage, dexterous robots with embodied intelligence is a key to closing this gap
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Argonne National Laboratory’s Accelerator Science Division is seeking a Postdoctoral Appointee to contribute to the development of a Sub- THz Collinear Structural Wakefield Accelerator
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aims to revolutionize the development of therapeutic platforms for IDPs, creating significant advancements in cancer research and treatment strategies. As part of a collaborative initiative with the
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candidate would be a PhD in geophysical sciences, computer science, or machine learning with experience in developing and verifying deep learning-based models for large dynamical systems (e.g. weather
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define requirements and performance specifications for future HEP/NP detector systems Perform detector concept development, system-level design, and optimization leveraging emerging computing architectures
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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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artifacts, and developing an independent research agenda in AI for science. Core responsibilities include: Leading research on foundation models, including problem formulation, algorithmic development, and
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in computational science, machine learning, and experience with synchrotron data analysis are strongly encouraged to apply. Position Requirements PhD completed in the past 5 years or soon to be
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contribute to research and model development to enhance the resilience of domestic and global supply chains for clean energy technologies. Lead technical and policy analysis to inform decision-makers
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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 science