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3.5 (full-time) 5 years (part-time)
Applications accepted year-round
Automated machine learning (AutoML) was proposed as an artificial intelligence-based solution for automating the tasks of applying machine learning to real-world problems. In this context, several algorithmic challenges emerge in a variety of ways, including societal bias embedded in training datasets, decisions made during the development of an ML system, and through complex evaluation loops that arise when an ML system is deployed in the real world. To address this challenge, this project aims to develop a dynamic strategy to decide when and on which ML model to conduct unfairness mitigation according to accuracy/fairness trade-offs.
Please include the project title and proposed supervisor in your application.
Watch: find out more about postgraduate study at the University of Hull
Open to fully self-funded full time / part time students only.
Applicants should have a minimum 2:1 degree in Computer Science or related subject. A taught MSc or Masters by Research in a relevant subject or relevant laboratory experience would be an advantage.
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