The goal is to generalize Bayesian automatic experimental design to multi-agent models consisting of an AI assistant and the human user, resulting in the AI assistant being able to decide its next actions. Tentative solutions involve developing fast probabilistic surrogates for existing simulator-type models and experimental design with approximate inference. The student will work alongside a team of researchers, supervised by a machine learning expert, and will have access to exciting application opportunities in both companies and academia.
Professor Sami Kaski from the Department of Computer Science has been appointed among the first Turing Artificial Intelligence (AI) World-Leading Research Fellow. The fellowships, named after AI pioneer Alan Turing, are part of the UK’s commitment to further strengthen its position as a global leader in the field.
Through his fellowship, Professor Kaski aims to overcome a fundamental limitation of current AI systems, that they require a detailed specification of the goal before they can help. Machine learning, where solutions to problems are automatically learnt from data, is a form of AI with great promise for addressing a number of challenges. This includes healthcare, where AI can detect patterns associated with diseases and health conditions by studying healthcare records and other data.
Further information can be found at:
https://www.ukri.org/news/global-leaders-named-as-turing-ai-world-leading-researcher-fellows/.
https://www.manchester.ac.uk/discover/news/new-human-ai-research-teams-could-be-the-future-of-research-meeting-future-societal-challenges/.
Informal enquiries regarding this topic and future projects can be directed to Professor Samuel Kaski ([Email Address Removed]).
Applications can be made via the standard process although we recommend checking your suitability before applying.
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