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Biomedical Engineering, Electrical Engineering, or a related fieldStrong background in MR physics Proficiency in computer programming Excellent written and oral communication skills Demonstrated ability
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. In particular, he/she will be expected to :• Select and evaluate the most suitable approaches from the wide range of machine learning and computer vision methods available in the literature, with
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Postdoctoral Research Associate ( Job Number: 26000369) Department of Computer Science Grade 7: - £ 38,784 - £46,049 per annum Fixed Term - Full Time Contracted Hours per Week: 35 Closing Date : 19
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 23 hours ago
Engineering stresses the application of science and engineering, mathematical analysis, and computer techniques to biomedical problems. The research and entrepreneurship of the faculty, students, and staff aim
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outputs, including: A return-of-data blueprint Prototype participant reports An evaluated framework for future implementation Your Profile Master's degree and PhD in computational biology, bioinformatics
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, Department of Computing invites applications for 1 postdoctoral researcher position in the field of medical artificial intelligence. The fixed-term position starts as soon as possible on mutual agreement, and
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brain health. This project combines MRI and EEG/MEG studies with behavioral, genetic, and clinical measures to yield a more complete picture of how processing speed is related to health outcomes
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the Centre for IoT and Telecommunications (CIoTT) in the School of Electrical and Computer Engineering. CIoTT is internationally recognised for excellence in wireless communications and signal processing and
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UiO/Anders Lien 24th April 2026 Languages English English English Postdoctoral position in Machine Learning and Computational Biology Apply for this job See advertisement About the position
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100% postdoctoral position within the Department of Radiology. The primary focus of this research position is to assist in innovative MR image reconstruction and pulse sequence methods. The successful