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Equinor. The position is in the Digital Signal Processing and Image Analysis (DSB) research group, Section for Machine Learning, Department of Informatics. For more information about the position, see https
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University of Pisa. The PhD Fellow will be affiliated with the Computer Networks Research Group (ComNet) at the department. The proposed PhD project aims to advance the field of 6G vehicular networks by
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the final exam. Desired qualifications: Experience in areas such as machine learning, computer vision, control sys-tems, perception, control engineering, or autonomous systems Familiarity with ROS (Robot
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-fellow-in-deep-learning-for-imaging Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/287578/phd-research-fellow-in-de… Requirements Research FieldComputer scienceEducation LevelMaster
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Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Norway Application Deadline 24 Nov 2025 - 23:59 (Europe/Oslo) Type of Contract Temporary Job Status Full-time Hours Per Week 37,5
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have experience with applications of machine learning and deep learning on medical image data that you have experience applying methods within generative artificial intelligence to medical images and
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. The PhD Fellow will be affiliated with the Computer Networks Research Group (ComNet) at the department. The proposed PhD project aims to advance the field of 6G vehicular networks by harnessing the AI
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development plan, specifying career goals and the competencies that the PhD fellow should acquire, no later than one month after commencement of the fellowship period. The department is responsible for ensuring
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the methods to innovations in close collaboration with Aker BP and/or Equinor. The position is in the Digital Signal Processing and Image Analysis (DSB) research group, Section for Machine Learning, Department
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. The following is considered important in the assessment: that you have experience with applications of machine learning and deep learning on medical image data that you have experience applying methods within