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disciplines; the prominence of chaos theory in the 1970s and 1980s; and its longer-term methodological and conceptual impact. The historical research is intended not simply as a parallel study, but as a source
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empirical evidence. The project runs for 33 months and comprises three research components operating in parallel, each led by a postdoctoral researcher and integrated through monthly team meetings and
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empirical evidence. The project runs for 33 months and comprises three research components operating in parallel, each led by a postdoctoral researcher and integrated through monthly team meetings and
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systems. In parallel, they will design and develop agentic AI and physics-aware AI models to accelerate discovery and deepen mechanistic insight in catalysis. This work will be carried out in close
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developing this program. We are also particularly interested in strengthening the group working the CMS Track Trigger or Forward Pixel Detector for the HL-LHC upgrades. A PhD in experimental high energy
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. Major responsibilites: The candidate will work independently to purify recombinant IDR constructs and label them for F19-NMR analysis. In parallel, the candidate will use Python for bioinformatics
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trajectory optimization, nonlinear programming, or genetic algorithms. High-performance computing (HPC), parallel numerical workflows, or GPU-accelerated model execution. Terms of Appointment This is a full
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. Participate in departmental seminars, workshops, and other academic events. The precise balance of activities will be determined by the candidate's expertise and the needs of the research program. Required
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 6 days ago
Postdoctoral Program website for application instructions and requirements: How to Apply | NASA Postdoctoral Program (orau.org) A complete application to the NASA Postdoctoral Program includes: Research proposal
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exploration and optimization of the process parameter space, as well as for adaptive, data-driven machine learning approaches to map the electrolysis process to a digital twin. In parallel, data workflows and