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of singularities, optimal control, and applications to macroscopic models of traffic flow. Teaching may be required. Education and Experience: Applicants must have recently completed a Ph.D. and have exceptional
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statistical methods. Supported by the ARPA-E TEOSYNTE and CERCA projects, this position is part of a national effort to improve nitrogen use efficiency on farms by modifying genetic pathways that control root
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Posting Details Position Information Job Title Postdoctoral Scholar Position Number PDS-Pharm-03-26 Vacancy Open to All Candidates Department EHH BSOM Pharmacology Department Homepage https
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improvements. Examples include optimizing the squeezing of the vacuum to minimize quantum noise, a prototype cryogenic interferometer, using machine learning for nonlinear feedback control, devising techniques
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Postdoc Appointment Term: 2026-2028 Appointment Start Date: Early 2026 Group or Departmental Website: https://med.stanford.edu/bronte-stewart-lab.html (link is external) How to Submit Application Materials
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computing resources, following best practices for reproducible research and version control (GitHub). Supervise and mentor undergraduate and masters student analysts working on projects across multiple teams
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individuals with disabilities to perform essential functions. Overview The individual will conduct experimental research, maintain and optimize specialized instrumentation, and contribute to data analysis
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++ and Python are required. Experience with control and optimization of power generation systems (e.g., wind power) is desirable but not required. Some experience with real-time control hardware is
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 14 hours ago
of the United States. A complete list of Designated Countries can be found at: https://www.nasa.gov/oiir/export-control . Eligibility is currently open to: U.S. Citizens; U.S. Lawful Permanent Residents (LPR); Foreign
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composites and develop science; and engineering methods for designing, scaling, optimizing and controlling relevant manufacturing processes. These positions will be based at the Rutgers’ School of Engineering