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Optimisation methods, such as mixed integer linear programming, have been very successful at decision-making for more than 50 years. Optimisation algorithms support basically every industry behind the scenes and the simplex algorithm is one of the top 10 most influential algorithms. Major...
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Skip to main content Main Menu - Primary Home Projects Supervisors Expression of Interest Contact Automated software testing and debugging with/without LLMs Primary supervisor Yongqiang Tian Research area Software Engineering The objective of this project is to design automated approach to detect...
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Skip to main content Main Menu - Primary Home Projects Supervisors Expression of Interest Contact Testing AI/LLM systems Primary supervisor Yongqiang Tian Research area Software Engineering In this project, we will develop automated approach to detect the defects in AI systems, including LLMs,...
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Machine learning is being used to make important decisions affecting people's lives, such as filter loan applicants, deploy police officers, and inform bail and parole decisions, among other things. Machine learning has been found to introduce and perpetuate discriminatory practices...
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Geomechanics program. In this role, you’ll oversee and conduct a range of standard and specialist testing, train and supervise students and researchers in safe equipment use and testing techniques, and ensure a
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of Machine Learning (ML) models across large-scale distributed systems. Leveraging advanced AI and distributed computing strategies, this project focuses on deploying ML models on real-world distributed
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time to meet deadlines. You will have advanced computer literacy, including experience with student administration systems or the ability to quickly learn new technologies. Strong analytical and problem
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leaders to align learning initiatives with strategic business goals. End-to-end program delivery – From concept to impact, you will manage programs with precision, leveraging data data to measure impact and
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these decisions? Required knowledge This project is open to candidates from diverse academic backgrounds, including computer science, data science, learning sciences, or educational technology. While prior
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, information science, criminology or media and communication studies and who have training in quantitative methods (e.g., regressions, non-parametric, parametric tests, Structural Equation Modelling) and/or qualitative