16 machine-learning-phd scholarships at UiT The Arctic University of Norway in Norway
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Stig Brøndbo 4th June 2024 Languages English English English Faculty of Science and Technology PhD Fellow in deep learning for spatio-temporal medical image analysis Apply for this job See
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The successful candidates will work at the machine learning group at UiT and will formally be affiliated with the Department of Mathematics and Statistics and collaborate closely with researchers at the Department
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machine learning and with strong programming skills, and with an interest in working in close collaboration with industry. Working environment: The project will be done in an interdisciplinary team
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deep learning. 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 of teaching and other
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responsibilities of the candidate: Developing innovative approaches: You will be responsible for developing machine learning and algorithms to manage and analyze next-generation sequencing data to understand its
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Associate Professor Mehrdad Rakaee. Key responsibilities of the candidate: Developing innovative approaches: You will be responsible for developing machine learning and algorithms to manage and analyze next
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machine learning and with strong programming skills, and with an interest in working in close collaboration with industry. Working environment: The project will be done in an interdisciplinary team
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Torbein Kvil Gamst 28th May 2024 Languages English English English Faculty of Science and Technology PhD Fellow in the intersection of information theory and deep learning Apply for this job See
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for feature extraction, which can serve as parameters in simulation. Alternatively, machine learning methods can be employed for comparison with the primary analysis-based approach. The objectives of this PhD
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for feature extraction, which can serve as parameters in simulation. Alternatively, machine learning methods can be employed for comparison with the primary analysis-based approach. The objectives of this PhD