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trials within the Computational Neuroscience Laboratory and the Addiction and Impulsivity Research group . This position will drive participant engagement across clinical trials of psychedelic-based
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package should be prioritised are surprisingly difficult computational tasks. State-of-the-art high-performance algorithms are used to calculate routes for the vehicles in order to minimise costs and
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operators for these notions. Over the past fifty years, such non-classical logics have proved vital in computer science and logic-based artificial intelligence: after all, any intelligent agent must be able
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sources of evidence such as audio, physiological activity and characteristics of the students). This project aims to develop methods for supporting teachers in reflecting on their positioning strategies in
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. Working under the direct supervision of the Group Lead, the Research Officer will assist in delivering high-quality experimental and technical research services to support the lab's program outcomes
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Anomaly detection methods address the need for automatic detection of unusual events with applications in cybersecurity. This project aims to address the efficacy of existing models when applied
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of policy conditions. The fellowship project is based on critical theories from fields like political economy and STS, alongside qualitative methods including document analysis and ethnography. Proposals
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anomalies in evolving graphs. In this research proposal, our aim is to explore the parallels of deep learning and anomaly detection in dynamic graphs. In particular we are interested to redesign deep neural
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(Honours) program. This student-centred course is designed to prepare graduates for meaningful, person-focused practice. You will lead and support teaching in areas that explore the psychological and
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operators for these notions. Over the past fifty years, such non-classical logics have proved vital in computer science and logic-based artificial intelligence: after all, any intelligent agent must be able