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of experience in project estimating or a similar role. Instructions to Applicants: For full consideration, applicants must apply for Project Management Estimator & Closeout Specialist at https://jobs.gmu.edu
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 19 hours ago
Carolina, US Hiring Range $16.00 per hour Proposed Start Date Estimated Duration of Appointment 6 months not to exceed 11 months Position Information Be a Tar Heel! A global higher education leader in
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, particularly for critical components such as cellulose, chlorides, and sulphates. Non-destructive examination (NDE) methods are essential to close these information gaps while preserving package integrity
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English into text using court reporting methods, a steno machine, Realtime technology, software and a laptop computer. Key Responsibilities Provides interpreting services primarily for instructional classes
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Science (EECS) Department of the School of Engineering and Computer Science.This position includes teaching, research activities and services to the community. TEACHING ACTIVITIES The successful candidate (M/F/X
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-Experience in particle physics phenomenology or related area - programming in C++ - programming in Python - fluent knowleage of English language Welcome: - experience in Monte Carlo methods and statistical
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-Experience in particle physics phenomenology or related area - programming in C++ - programming in Python - fluent knowleage of English language Welcome: - experience in Monte Carlo methods and statistical
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interdisciplinary team of engineers, computer scientists, and life scientists Present your work at international conferences and learn about state-of-the-art methods in machine learning, reinforcement learning and
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. Stefanos Zafeiriou can be found at https://wp.doc.ic.ac.uk/szafeiri/ . Research Associate: A PhD (or be close to completion) in an area pertinent to the subject area, i.e. computer vision, machine learning
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biosensor imaging, and behavioral pose estimation. The specialist will integrate multimodal datasets and apply advanced statistical and machine-learning methods to uncover relationships between gene