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Better Personalization of Deep Learning-Enhanced Hearing Devices - Royal National Institute for Deaf People (RNID) EPSRC Centre for Doctoral Training in Sustainable Sound Futures PhD Research
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of computer vision and deep learning for advanced air mobility. Immerse yourself in innovative research fields, including: 2D semantic/panoptic (video) segmentation and object recognition 3D semantic/panoptic
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biodiversity and sustainability research. The initial objective is to use deep learning techniques to perform acoustic species identification in real-time on low-cost sensing devices coupled to cloud-based
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In manufacturing, a wide variety of use cases exist where Deep Learning (DL) and Machine Learning (ML) are successfully applied. Examples of use cases include the production of rockets, stem cells
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Although deep learning has produces state of the art results on many problems, it is a data hungry technology requiring a lot of human supervision in the form of annotated data. Potential PhD topic
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Over the past decades, we have witnessed the emergence and rapid development of deep learning. DL has been successfully deployed in many real-life applications, including face recognition, automatic
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of the AAAI Conference on Artificial Intelligence (Vol. 26, No. 1, pp. 267-273). - Blau, T., Bonilla, E. V., Chades, I., & Dezfouli, A. (2022, June). Optimizing sequential experimental design with deep
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Research Associate (Computer Engineering/Computer Science/Engineering/Mathematics/Biology/Chemistry)
of faculty, students and alumni who are shaping the future of AI, Data Science and Computing. The group focuses on the development of deep learning technologies for the advancement in medicine and healthcare
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Job Purpose The Professional Officers Division (POD) houses a centralized pool of academic staff under the Professional Officers scheme. Professional Officers come with specialised and deep
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-campus for the Spring 2026 Semester (01/05/2026 - 04/26/2026) Course: Search Engines and Data Mining Lecture & Lab This course provides a comprehensive introduction to neural networks and deep learning