Understanding the self in cognition and its behavioural correlates

Self biases are pervasive in our decision making and even in the way we see the world. Evaluating the properties of these biases provides a critical way of trying to understand what we mean by the self – a longstanding quest to numerous disciplines (e.g., psychology, behavioural science, philosophy, neuroscience). This project proposes a new hypothesis of self-biases – self acts an ‘integrative hub’, providing a form of glue that enhances information processing, leading to optimal behaviours. The project will assess this new account and its behavioural correlates.

We wish to recruit a highly motivated phd candidate to join a collaborative team. This 3-year PhD studentship will deliver student centre training including programming skills and advances statistical and machine learning analyses, with an explicit emphasis on interdisciplinary research (experimental psychology, behavioural science, computational sciences). Therefore, the project would suit a graduate who has experience in at least one of these disciplines – psychology, behavioural science, neuroscience, or computing science, and would receive training on the others. 

Candidates should have a postgraduate qualification (e.g., MRes, or MSc with at least 90 credits of methodology, or can demonstrate substantial experience) in psychology or related fields (e.g., Neuroscience, Biomedical engineering, Computer Science).

In addition to the academic entry requirements, successful applicant are also required to satisfy essential background and knowledge:

Knowledge of self literature

Experience in experimental design or quantitative methodology in assessing information processes