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relevant PhD/DPhil (or be near completion) in machine learning, computer vision or biomedical image analysis, together with relevant experience. Publications/presentations in top conferences and journals in
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such as reality capture, quality assessment, 3D modelling, computer vision and computational design in the built environment, operating at the intersection of construction informatics, engineering, and
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(UTC) Type of Contract Temporary Job Status Not Applicable Hours Per Week 40.0 Is the job funded through the EU Research Framework Programme? Not funded by an EU programme Is the Job related to staff
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
one of the leading public research institutions in the country. UNC-Chapel Hill offers postdocs comprehensive medical and vision coverage , paid leave, and benefits and services that support
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encouraged to apply. Previous experience working with optical imaging and computer vision is a strong plus. The successful candidate will be jointly based in the Department of Urology at the Stanford
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 days ago
one of the leading public research institutions in the country. UNC-Chapel Hill offers postdocs comprehensive medical and vision coverage , paid leave, and benefits and services that support
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fractures and the cause using X-Ray images. The successful candidate will be responsible for conducting cutting-edge research in machine learning and computer vision applied to medical data. Responsibilities
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research in Computer Vision and Machine Learning and the potential applications to Biometrics, Explainability, Security, and Media Forensics (among others)? If so, we have the perfect opportunity for you! We
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completing a Ph.D. degree will also be considered. Desirable qualifications include strong numerical simulation skills, experience in computer vision or 3D reconstruction, excellent written and oral
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the performance and energy efficiency of the developed models. Collaborate with interdisciplinary teams to apply these models to real-world problems in areas such as natural language processing, computer vision