10 assistant-professor-computer-science-data-"https:"-"https:"-"https:"-"UCL"-"UCL" Fellowship positions at OsloMet
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of interdisciplinary initiatives across the university. Department of Computer Science has an available 100% temporary position as Phd fellow in assistive technology and social innovation for older adults. Your main
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for extended research stays abroad . Qualification requirements Master's degree within Electronics Engineering, Computer Engineering or equivalent related disciplines. The degree must normally include 120
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Campus in Viken. The Department of Computer Science offers three bachelor’s degree programmes, a master’s degree programme, and is part of a cross-departmental PhD program. Academic staff at the department
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research stays abroad . Qualification requirements Master's degree in Robotics, Cybernetics, Artificial Intelligence, Computer Science, Electrical Engineering, Aerospace Engineering, Engineering Physics
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Campus in Viken. The Department of Computer Science offers three bachelor’s degree programmes, a master’s degree programme, and is part of a cross-departmental PhD program. Academic staff at the department
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, reliability engineering, biomedical engineering, data science/machine learning, or equivalent related disciplines. The degree must normally include 120 credits (ECTS). If the master’s degree includes fewer than
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Campus in Viken. The Department of Computer Science offers three bachelor’s degree programmes, a master’s degree programme, and is part of a cross-departmental PhD program. Academic staff at the department
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on the doctoral programme’s website (Engineering Science - OsloMet ). Written and oral proficiency in English (Language requirements for employees at OsloMet ) Admission to the PhD programme in Engineering Science
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at OsloMet ) Admission to the PhD programme Innovation for Sustainability at the Faculty of Technology, Art and Design is a prerequisite for employment in the position. An application for admission to the PhD
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of maintenance. The project aims to develop an integrated decision-support framework that combines inspection images, sensor data, and engineering interpretation to enable more transparent, evidence-based