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are seeking a Research Data Manager who will be responsible for the management of large, complex data sets for the assigned project/study. The Research Data Manager is responsible for. Data quality assurance
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of LHC data, based on solid C++ and Python expertise, is strongly appreciated. Ability to work in a large international collaboration is a must. Fluency in English, speaking and writing (B2 minimum) is
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North Carolina A&T State University | Greensboro, North Carolina | United States | about 19 hours ago
problems involving big data, extensive computations, and complex modeling, simulation, optimization and visualization. The M.S. in Data Science and Engineering is an interdisciplinary graduate program
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carried out within an interdisciplinary team, involving economists, management scholars, and computational chemists. Where to apply Website https://www.santannapisa.it Requirements Additional Information
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description. The applicant must have excellent professional proficiency in English (written and spoken). Required: Strong knowledge of how to use AI and large language models (LLMs) for data extraction
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, disability, age, genetic information, veteran status, marital status, and/or political affiliation in its programs, activities, or employment. See https://go.unl.edu/nondiscrimination Minimum Required
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2 Apr 2026 Job Information Organisation/Company CNRS Department Institut de Recherche en Informatique Fondamentale Research Field Computer science Mathematics » Algorithms Researcher Profile First
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, large-scale, and automated technologies for collecting and utilizing information related to the structural health of bridges in support of decision relevnt to seismic performance management. The work will
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Posting Details Student Title Classification Information Quick Link https://chapman.peopleadmin.com/postings/39476 Job Number SE190624 Position Information Department or Unit Name Chapman Radio
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people where they are. A typical work week will include a large amount of programming and data pipeline development, along with meaningful collaboration, data management, requirements gathering