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the area of end-to-end modular autonomous driving using computer vison and deep learning methods. This includes developing an efficient and interpretable image processing, vision-based perception and
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contributions towards external activities Demonstrated expert knowledge in machine learning, AI, and bio-signal processing Experience in conducting research projects, with demonstrated high-level written and oral
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This project aims to develop robust algorithms capable of identifying and analyzing fingertips extracted from both static images and video footage. Machine learning techniques, particularly computer
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for whom English is not their primary language. Strong computer skills including the understanding of student management systems and Microsoft Office suite of products. Note: The successful applicant will be
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: Contribute to the design, manufacture and delivery of a prototype field-deployable quantum sensing device. Support the development of project plans and schedules and participate in planning processes as
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. Knowledge or experience of Robot Operating System (ROS), tools for training and using deep learning algorithms and in image processing and computer vision algorithms and solutions using open-source software
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the below selection criteria (maximum 2 pages): Completion of, or working towards, a degree or certificate in Accounting/Finance and/or relevant experience. Strong computer skills including Microsoft
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at St Lucia in the Business School. Key responsibilities will include: Engineer, prototype, validate and deploy statistical, machine learning models and analytic solutions to solve challenging problems
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, student mentoring and student experience. Possess sound computer skills to email, access databases, MS Officer and or other relation Learning Management Systems. Current practical experience (currency
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mechanical loading of such samples. The focus of the PhD project will be to use machine learning techniques to better understand the interplay between the crystal orientations and deformation patterns in a