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to circumvent this limitation by learning patterns in unlabelled medical images and then leveraging them for downstream tasks. In this project, you will develop novel unsupervised machine learning methods
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to develop novel, bio-inspired neural networks that flexibly and robustly control locomotion in multi-limbed robots. "Self-organised clocks for reliable spiking computation" (Supervisor: Prof Timothy O'Leary
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We are a world class research-intensive university. We deliver teaching and learning of the highest quality. We play a leading role in economic, social and cultural development of the North East of
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railway earthworks. Additionally, the project will integrate environmental data through data fusion and develop automated machine learning tools for anomaly detection and risk assessment. The effectiveness
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are below but also own ideas in the topic area are welcomed: Understanding the impact of accessing appropriate Housing – i.e. disabled facilities grant Role of education professionals in caring for children
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verification-inspired benchmarking (Frank et al., arXiv:2024) using blind testing approaches. The student will develop verification-based benchmarking approaches for digital quantum computers with realistic
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labs framework. This studentship will include cohort-based training and activities, enabling students to gain wider skills and develop valuable personal and professional networks. Project Description
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employment practices for the advancement of gender equality. We also hold a Race Equality Charter Bronze award in recognition of our work towards tackling race inequality in higher education REC. We
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We’re here to create and harness knowledge, to deliver opportunity for everyone. About the Opportunity Based in the Faculty of Education, this is an excellent opportunity for a talented and
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, through not requiring them to lose substantial educational opportunities. This approach has also been used successfully with adults in the workplace receiving treatment online without impact on their work