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Overview This PhD project will take a comprehensive approach to exploring how corporate sustainability disclosure practices evolve in response to the integration of Machine Learning (ML) within
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machine learning framework by leveraging a dynamical systems perspective for designing stimulation protocols (SPs) towards improved customised medical treatments. More specifically, we shall deploy
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candidate will develop machine learning and algorithmic design skills. The candidate will gain valuable multidisciplinary skills in the area of machine learning and data analytics methods and their
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the development of climate change models of fashion supply chains and the design of computer model laboratory experiments (with students) that will aim to determine what and how participants learn from these models
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, such as aspects of Social Identity Theory, Social Learning Theory, behavioural integrity, ethical behaviour, psychological safety, and psychological empowerment, this PhD will seek to identify how
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prediction model; specifically, those models that utilize network analysis and machine learning techniques. The aim of this project is to attempt to evaluate the relative strengths of this new strand
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the use of AI and machine learning for the identification of explosives and drugs in security imaging. It will combine the properties of X-ray absorption and diffraction imaging to give the AI and machine
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and other sleep technologies, and motion capture sensors to collect and analyse data. Machine learning tools will be used to establish relationships between mattress design, individual specifications
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to publish their research at top-tier machine learning conferences (such as ICML, ICLR, NIPS etc.). Supervisory Team Archontis Giannakidis Jonathan Crofts Amin Al-Habaibeh Entry qualifications We invite
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the BBB, providing lifecourse gene therapy treatment for neurological disorders. This project introduces a novel machine-learning approach to optimize AAV capsids by predicting structural modifications and