We develop probabilistic machine learning methods for helping other agents make better decisions, ultimately human agents in ongoing applications in science and engineering. We use multi-agent formulations to define the assistance problems solved by these agents, and probabilistic modelling for defining the problems the agents together solve in the world. The project has flexibility in how much to focus on multi-agent reinforcement learning, new models of human behaviour, or modelling the scientific and engineering problems to be solved collaboratively. For all these, we are working with top-notch collaborators. I am looking for a student with experience in probabilistic machine learning and preferably reinforcement learning. No formal experience with cognitive science or application domains is required, but is a plus. Additional knowledge in any of the following will be helpful: game theory, multi-agent RL, Bayesian RL, computational rationality, and inverse reinforcement learning.FundingThis is a fully funded project via the Department of Computer Science (£18,622 per annum as per from 2024) as per details and update published on UKRI website: Minimum amounts for studentship stipends and allowances. Self-funded applicants can be considered subject to feasibility.Entry requirementsThe standard academic entry requirement for this PhD is an upper second-class (2:1) honours degree in a discipline directly relevant to the PhD (or international equivalent) OR any upper-second class (2:1) honours degree and a Master’s degree at merit in a discipline directly relevant to the PhD (or international equivalent).How to applyYou will need to submit an online application through our website here: https://uom.link/pgr-applyWhen you apply, you will be asked to upload the following supporting documents: • Final Transcript and certificates of all awarded university level qualifications• Interim Transcript of any university level qualifications in progress• CV• You will be asked to supply contact details for two referees on the application form (please make sure that the contact email you provide is an official university/ work email address as we may need to verify the reference)• English Language certificate (if applicable)Your application form must be accompanied by a number of supporting documents by the advertised deadlines. Without all the required documents submitted at the time of application, your application will not be processed and we cannot accept responsibility for late or missed deadlines. Incomplete applications will not be considered. If you have any queries regarding making an application please contact our admissions team [email protected] you applyWe strongly recommend that you contact the supervisor to discuss the application before you apply. Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. We know that diversity strengthens our research community, leading to enhanced research creativity, productivity and quality, and societal and economic impact. We actively encourage applicants from diverse career paths and backgrounds and from all sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation and transgender status.We also support applications from those returning from a career break or other roles. We consider offering flexible study arrangements (including part-time: 50%, 60% or 80%, depending on the project/funder).