142 phd-studenship-in-computer-vision-and-machine-learning Fellowship positions in Norway
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invites applicants for four PhD Fellowships in subsurface characterization within geosciences, reservoir engineering, molecular modelling, and machine learning at the Faculty of Science and Technology
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of the position is to complete research training to the level of a doctoral degree. Admission to the PhD programme is a prerequisite for employment, and the programme period starts on commencement of the position
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contribute to cargo selectivity. The position is for a period of four years. The nominal length of the PhD programme is three years. The fourth year is distributed as 25 % each year and will consist
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must take part in the University’s/ Faculty’s/ Department’s approved PhD program and is expected to complete the project within the set fellowship period. The main purpose of the fellowship is research
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will be adapted to the candidate’s background and the evolving needs of the center. Possible directions include the application of rock physics models, Bayesian inversion methods, and machine learning
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machine learning Personal and relational qualities will be emphasized. Motivation, ambitions and potential will also count when evaluating the candidates. Special requirements for the position
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machine learning. Magnetic Resonance Imaging. Laboratory experience from porous media research related to physics and/or chemistry. Personal and relational qualities will be emphasized. Motivation
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, Computer Science, or Machine Learning) The Master’s thesis must be included in the application It is a requirement that the successful applicant is granted admission to the university’s doctoral program in
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physics models, Bayesian inversion methods, and machine learning algorithms in the electromagnetic context. Qualifications and personal qualities: Applicants must hold a master’s degree (or equivalent) in
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position The USN School of Business has three vacancies for 100 % positions as PhD Research Fellows in the PhD programme in Management from 01.01.2026. The positions will be affiliated with one