Metacognition broadly refers to the ability to accurately reflect on one's own mental states, and is important for adaptive behaviour. For example, metacognition enables us to identify our mistakes and to switch strategies when they are failing. Mentalising and Theory of Mind refer to the ability to infer the mental states, knowledge and beliefs of others. For obvious reasons it is also important for adaptive behaviour: successful interactions with others requires us to have at least some understanding of their beliefs and knowledge, or lack thereof ("I changed my plans and am no longer free for dinner; I should let my housemate know.").  

Both metacognition and mentalising have received a lot of attention in cognitive neuroscience, however there has been far less work examining the role of uncertainty in mentalising: to what degree are we able to accurately reflect on our inferences about others? What are the neural and computational correlates of metacognition for mentalising? The project will take a “bottom-up” approach to address these questions, investigating the extent to which we can understand and model metacognition for mentalising using simple systems and processes (e.g. the perceptual/motor systems and reward learning). This approach contrasts with those that invoke specialised systems such as the mirror neuron system. 

The project will involve both designing and running behavioural experiments with human participants and computational modelling. There is also the option of also using brain imaging (e.g. EEG), physiological recordings (e.g. eye-tracking) and/or machine learning. The student will have freedom to choose the particular direction they take in their research. Options include investigating metacognition in economic games (e.g. trust games), in collaborative or competitive games (e.g. board games), or in social interactions.  

The project will suit a rigorous and methodical student with a background in artificial intelligence, cognitive science, experimental psychology or a related discipline. Confidence with mathematics and statistics is essential. The research will be conducted according to the principles of Open Science (pre-registration of analysis plans, freely sharing data and code) so enthusiasm for this is important as well. The project will involve a lot of programming, so previous experience with languages such as python, R, MATLAB or similar is an advantage but a willingness to learn is sufficient. 

This scholarship is available to UK, EU and overseas applicants. 

Eligible candidates will have an upper second-class (2:1) undergraduate honours degree (or equivalent qualification) in a related field. 

The University of Sussex believes that the diversity of its staff and student community is fundamental to creative thinking, pedagogic innovation, intellectual challenge, and the interdisciplinary approach to research and learning. We celebrate and promote diversity, equality and inclusion amongst our staff and students. As such, we welcome applicants from all backgrounds.

Please clearly state on your application that you are applying for the Computational Modelling of Metacognition for Mentalising and Social Interactions scholarship under the supervision of Dr Maxine T Sherman. 

Please ensure you application includes each of the following: 

• Research interests or a research proposal. For guidance on preparing a proposal, please see here. 
• Your CV.
• Degree certificates and transcripts. 
• 2 references, including a minimum of 1 from any institution studied at within the last 5 years.
• If your first language is not English you will need to demonstrate that you meet the University’s English language requirements, see here for details of our accepted documentation.