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Field
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related field in hand by the time of the appointment. Strong background in distributed control, optimization, or multi-agent systems. Proven track record of high-quality publications. Proficiency in
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 2 hours ago
tools for spacecraft applications, specifically leveraging topology optimization and lattice structures. Building upon prior work at JPL, including the open-source lattice design tool UnitcellHub and an
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for the fundamental understanding and engineering design of safe autonomy for autonomous vehicles. The post-doctoral researcher should have a strong background in autonomous vehicles, optimal control, differential
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of a team member who can optimally get along with a varied population of diverse audiences. We are looking for someone who shares our values and who will support the mission of the university through
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
domains. You will play a key role in shaping infrastructure that enables expressive querying (e.g., via the Model Context Protocol) and optimize integrated data for downstream AI/ML applications such as
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at temperatures of 50 mK-350 K and at fields of up to 15 T with emphasis on the development of new sensing protocols optimized for high-field and low temperature environments. In addition, these sensors will be
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of a team member who can optimally get along with a varied population of diverse audiences. We are looking for someone who shares our values and who will support the mission of the university through
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data analysis/spectral image processing. Use of data analytics or machine learning to guide process design and optimization. Job Family Postdoctoral Job Profile Postdoctoral Appointee Worker Type Long
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applications of stochastic and (distributionally) robust optimization (SRO) and foster interdisciplinary research collaborations to address emerging real-world problems in various application domains, including