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Field
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for the position of assistant professor in the project NCN MAESTRO "Challenging problems in partial differential equations inspired by cutting-edge algorithms in statistics and machine learning
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collection methods for external data (e.g. web scraping) to collect data for use in modelling and analysis. Develop analytic plans, engineer supporting algorithms, write new functions or applications in
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the next generation of distributed software infrastructure for JGI, represent the JGI in relevant reviews, national and international activities, and within the broader DOE National Laboratory system
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distribution can predict both single AZ and whole synapse function at the neuromuscular junction (NMJ). Adapt and convert an existing, experimentally validated MCell simulation of mammalian NMJ AZs into Python
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literature. Foundational Algorithms for AGI AGI will not emerge from scaling existing models alone; it requires a new algorithmic foundation for learning, reasoning, and adaptation. This research area is
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computational tools for quantifying electromagnetic field distributions down to the fundamental atomic scale. The project will build on recent developments in inverse scattering methods, including ptychography
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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and
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A PhD studentship is available to work on Logistics automation. The student associate will work in the Intelligent Logistics Group within the Distributed Information and Automation Laboratory (DIAL
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A PhD studentship is available to work on Logistics automation. The student associate will work in the Intelligent Logistics Group within the Distributed Information and Automation Laboratory (DIAL
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developing new methods and techniques that will improve standard ML algorithms so as to achieve good performance outside their training distribution, by treating high-dimensional problems as an explicit