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product sizes and enabling direct on-site manufacturing. The successful candidate will explore innovative methods to realize large-scale on-site 3DP by addressing two key technical challenges: 1) How
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key area of patient safety that can be improved with the use of computer vision approaches to system analysis. For many clinical procedures there can be multiple deviations in service delivery, which
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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health, and bioinformatics. You will apply advanced AI methods - from classical machine learning to large language models and agent-based AI - on large-scale healthcare datasets, including structured
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collaborative project that spans multiple continents. You will contribute to the development of new chronobiological analytics on existing data, design experiments to collect novel chronobiological data, engage
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will be tasked with the development of new models for the early detection of CIN cancers, applying bleeding edge computational methods and machine learning approaches to improve detection and
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Dysregulation of the complement system is increasingly recognised as a key driver of neuroinflammation and neurodegeneration in progressive CNS disorders, including multiple sclerosis and epilepsy
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into the genomics of population structure and speciation in the Malawi cichlid genus Labeotropheus. This post will build on past work in which over 1000 samples of Labeotropheus from multiple species/populations have
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. However, inefficiencies in wind turbine control and maintenance lead to increased operational costs and reduced energy output. Traditional maintenance methods rely on reactive or time-based servicing, which
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Human Behaviour in projects targeting social good. Research at N/LAB focuses on the development and application of innovative computational methods using Big Data, Behavioural Science and Machine Learning