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Postdoctoral Associate to work on a fascinating project focused on the development machine-learning powered digital twin system for the structural performance of civil engineering structures. The project is a
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image analysis and sensor technologies (e.g. RGB/NIR) for textile production, as well as using machine learning for process optimisation and performance prediction from fibre to finished product
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Computer Engineering. Expertise in computer vision algorithms and image processing techniques (such as object detection, segmentation, and feature extraction). Proficiency in deep learning frameworks such as
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with artificial intelligence (machine learning/deep learning) Essential Application/interview Experience with classical image processing techniques (e.g. classification/segmentation/registration
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practical in assisting all projects. Additionally, there can be engineering advantages gained if projects can be aware of the technologies and products every project is dealing with. Sharing lessons learned
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of Biomedical Engineering (SBME). The successful candidate will work on advanced machine learning applications in computational pathology, medical imaging, and clinical text analysis. They will be expected
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interdisciplinary team with clinicians and engineers; You have strong programming skills in Python; You have knowledge of medical image processing, and machine learning and deep learning techniques; Written and
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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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certified airframe and powerplant mechanic, performing inspections and repairs of FAA required inspections of all aircraft assigned to the School of Aviation & Transportation Technology. Will utilize
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Technology POSITION DESCRIPTION: LeTourneau University invites applications for adjunct faculty members qualified to teach manual machining and/or CNC machining during the academic year. Classes are located