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Field
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, computer science, or ecology with a quantitative, and empirical orientation. Required knowledge, skills and abilities: Ability to multi task and work cooperatively with others Good communication and computer skills
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of Applied/Computational Mathematics. Research topics of interest include numerical methods for scientific machine learning and AI, and their applications to various science and engineering disciplines
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REcherche BEI) program. The successful candidate will join the SVV research group, headed by Prof. Domenico Bianculli. The group focuses on the development and design of reliable, safe, and secure software
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for activities in the Zero-G Lab and contributing to the Black-Hole Lab at Redwire Space Luxembourg for Hardware in the loop emulation of on-orbit scenarios. Responsabilities: Investigate existing verification and
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Staff Job Description Job Responsibilities 50%: Lab research - Design, plan, conduct and coordinate experiments in a wet lab as well as using computers. 20%: Communication - Keep detailed records of data
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 5 hours ago
been as much focus on connecting science objectives directly to the developmentof an engineered system. Systems engineering practices emphasize verification: the process of ensuring that a system meets
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based upon satisfactory performance. Job Requirements: Required: a Ph.D. (expected or obtained) in statistics, engineering, computer science, mathematics, economics, operations research, or a related
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proposals. -Other duties as required. Required Education: -Ph.D. in Soil and Crop Sciences, Statistics, Data Science, Computer Science, Agricultural Engineering, or a closely related field. Required Knowledge
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Massachusetts Institute of Technology, MIT Kavli Institute Position ID: MIT-MIT Kavli Institute-PAMILLHOLLAND [#30922] Position Title: Position Type: Postdoctoral Position Location: Cambridge
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/ Deep Learning (particularly Computer Vision or 3D perception) Verification & Validation (V&V) of advanced algorithms, software or systems Formal Methods Safety Engineering / Safety-Critical Systems