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captioning. Development of causal reasoning tools, including causal inference, counterfactual analysis, causal discovery. Development of deep learning methods and theory. Development of computer vision methods
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existing technologies, right through to the tested prototype. The Data-based Methods team at Fraunhofer ENAS develops real-world applications using AI, machine learning and computer vision. The main focus is
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on computer vision in the new £7.7M EPSRC-funded “TORUS” Programme Grant, where cameras and machine learning at the edge will be characterising symptoms of Parkinsons Disease. You will also be a key contributor
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The College of Computing & Data Science (CCDS) invites applications for the position of Research Associate. We are seeking researchers to work on a computer vision project. The position is for one
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implementation. Its vision is a world where health informatics can facilitate the appropriate, evidence-based use of antibiotics. This ambitious programme of work will be delivered across Liverpool over the next 2
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candidates will be involved in a project that is related to generative design. Key Responsibilities: To independently undertake research in computer vision and machine learning. To produce research reports and
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candidates will be involved in a project that is related to generative design. Key Responsibilities: To independently undertake research in computer vision and machine learning. To produce research reports and
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-task and pay attention to detail TOOLS AND EQUIPMENT USED: Knowledge of operation and use of various office equipment including, but not limited to: personal computer, including spreadsheet and word
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detection. Develop graph neural network theory. Develop sequence modeling theory. Develop deep learning methods and theory. Develop computer vision methods. Job Requirements: Master's degree or higher in
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vision loss on a statewide basis. Incumbent will oversee work experience program for visually impaired students at the SD School for the Blind and Visually Impaired, by establishing and supervising work