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, and coding skills. Excellent communication (both writing and oral) and interpersonal skills. Can work independently or in a team. Willingness to take initiative. Application Instructions Applicants
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distributed decision-making. Applicants must have a PhD in Electrical Engineering, Mechanical Engineering, Computer Engineering, Applied Mathematics, Mathematics, or a closely related discipline, and are within
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National Energy Technology Laboratory (NETL) | Morgantown, West Virginia | United States | about 2 hours ago
. The first two recommendations received will be attached to your application for review by NETL. You may click the "send" (paper airplane) button to send the recommendation request email immediately after
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written English skills (B2 level or equivalent, certified), ability to read, understand, and write in scientific English. 7. Knowledge and ability to operate computer software. 8. Analytical thinking
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an interim review approximately two years after hiring. Probationary period:Probationary period present Probationary period description:In principle, the first two months of employment are considered a trial
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to three orders of magnitude. Bridging this gap requires more accurate calculations and realistic models, and currently, there is no first-principles investigation of spin dynamics on surfaces. This project
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unit’s machine shop, as needed. Learning Objectives: Under the guidance of a mentor, you will: Develop an understanding of the principles of remote-sensing technologies used to monitor grain quality and
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Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 09-Jul-26 Location: Abu Dhabi Categories: Academic/Faculty Internal Number: 189065 The Laboratory for Computer-Human
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Description The Laboratory for Computer-Human Intelligence (CHI-lab, https://www.x-labs.xyz) in the Division of Engineering, New York University Abu Dhabi, is seeking a highly motivated Post
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design. Perform large-scale computational screening using first-principles calculations and machine-learning potentials. Analyze structure–property relationships and extract scientific insights from AI