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Schedule: Monday – Friday, 8 a.m. – 5 p.m. Summary The Cheng Lab in the Department of Medicine, Section of Epidemiology & Population Sciences is searching for highly motivated and talented post-doc
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. Location of Vacancy Part/Full Time Full Time Hours per Week 37.5 Work Schedule Monday – Friday 8:30 AM to 5:00 PM Must be willing to work a flexible schedule to meet the needs of the department. Type
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 6 hours ago
. around Mars) through a set of cooperating communications relays, the burden on DSN scheduling can be significantly reduced. The use of frequency division (OMSPA) enables all probes communicating through
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algorithmic performance. For instance, the scheduling problems that an electric grid operator faces will change daily, but not drastically: although demand will vary, the network structure will remain largely
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on using unstructured and overset meshes with high-fidelity algorithms to obtain scale-resolved data. Candidate will also post-process data using data-driven and physics-driven methods to extract fundamental
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Position Location: Richmond Campus Driver Classification: Non-Driver FLSA: Exempt Schedule Type: Full Time (37.5 hrs per week or more) Hours Per Week: 37.5 Additional Schedule Details: Posted Salary Grade
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 6 hours ago
cost and schedule of every space mission. Traditionally, verification is treated as a binary outcome in that the system is tested against a set of criteria and determine to either meet or not meet it
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place technologies and to develop digital twin algorithms to assist clinicians in developing treatment plans. Analyzes complex sensor data, works with a multidisciplinary team to develop health digital
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closely with a small, dedicated team, you will: Design and implement SLAM-based navigation algorithms for GPS-denied forest environments (45%) Develop multi-sensor integration software for LiDAR, cameras
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across AI, incorporating insights from algorithm development, systems engineering and architecture, human psychology, sociology, law, science and technology studies, economics, and policy studies. Faculty