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Short description The PhD project is focused on recommended design and engineering principles of totally renewable microgrids with the ambition to outperform traditional networks reliability
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As education systems increasingly adopt AI to support teaching and learning, the automation of assessment and feedback processes has emerged as a critical area of innovation. Large-scale learning
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promising results in building prediction models, they are typically data-centric, lack context, and work best for specific feature types. Interpretability is the ability of an ML model to identify the causal
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Despite the popularity of providing text analysis as a service by high-tech companies, it is still challenging to develop and deploy NLP applications involving sensitive and demographic information
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is carried out within the LHCb collaboration that runs one of the four large experiments at the Large Hadron Collider at CERN as well as towards future collider developments. I supervise a number of
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This project is similar in flavour to the Conscious AI project but rather than come from a Philosophical/Neuroscience/Math/Theory angle, this project aims to build self-aware neural networks
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psychopathological features of the illness, the moderate efficacy of existing treatments suggests we do not yet have a full understanding of what is core to these illnesses, nor how best to heal from them. This PhD
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Introduction Rodent behavioural testing is the study of the neural mechanisms underlying emotions [1]. It is used in the study of almost all mental conditions, including PTSD [2], OCD [3] and
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systems. The fast growth, practical achievements and the overall success of modern approaches to AI guarantees that machine learning AI approaches will prevail as a generic computing paradigm, and will find
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Research data governance is an under-explored issue, and technical infrastructures to support the transparency and control of data collected in human research studies (from medicine to social