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activities. Specific Requirements • PhD in physics, nuclear engineering or material science • Coating fabrication by sputtering (e.g., magnetron sputtering; thin-film deposition workflows). • Materials
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 11 hours ago
Permanent Staff (EHRA NF) Working Title IT Analyst/Programmer - 2 (Haendel) Appointment Type EHRA Non-Faculty Position Number 20065940 Vacancy ID NF0009590 Full Time/Part Time Full-Time Permanent FTE 1 Hours
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 12 hours ago
substitution. May require terminal degree and licensure. Required Qualifications, Competencies, and Experience Bachelor’s degree in Computer Science, Software Engineering, or a relatied field; or an equivalent
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shaping the future. https://nusit.nus.edu.sg/ Job Purpose We are seeking an experienced Application Development Manager to oversee one or more software development teams in NUS. This role will report into
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About Jonesboro, Arkansas: Jonesboro is the regional hub of Northeast Arkansas for healthcare, entertainment, business, advanced manufacturing, software development, and civil engineering applications. It
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Professor in Geospatial Engineering. The position will be in the Department of Civil, Environmental, and Geospatial Engineering. Applicants with the required education, experience, knowledge, skills
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Posting Details Posting Details Position Title Assistant Professor in Computer Science for Software Engineering External Link to Posting https://jobs.uncw.edu/postings/38734 College College
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community to enable innovation, learning, discovery, and service. The IT Infrastructure division provides knowledgeable system design and administration, software engineering, and operational support for
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background and research publications. As to the requirements for lecturer, please refer to Recruiting Notice on Teaching and Research Positions, released by Human Resources Department of NJFU at: https
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requirements and focusing on data-value maximisation. This project will utilise innovative machine learning methods and tools from process systems engineering to simultaneously optimise product quality and the