The School of Biological and Behavioural Sciences at Queen Mary is one of the UK’s elite research centres, according to the 2021 Research Excellence Framework (REF). We offer a multi-disciplinary research environment and have approximately 180 PhD students working on projects in the biological and psychological sciences. Our students have access to a variety of research facilities supported by experienced staff, as well as a range of student support services.
Rani Moran's Lab studies decision making, memory, attention. Our vision that a better understanding of these processes will allow us to develop interventions to promote their effective usage. We sepcialize in developping computational models for cognitive processes, which illuminate the innter workings of cognitive mechanisms.
Our PhD students become part of Queen Mary’s Doctoral College which provides training and development opportunities, advice on funding, and financial support for research. Our students also have access to a Researcher Development Programme designed to help recognise and develop key skills and attributes needed to effectively manage research, and to prepare and plan for the next stages of their career.This project will foster diverse skills including: Experimental task design, complex statistical analysis, computational modelling, working in a team, programming of online experiments, MATLAB, and academic writing.
Reinforcement Learning (RL), is a multidisciplinary filed with implications for a broad range of disciplines including Psychology, Neuroscience, Medicine, Computer Sciences, Machine Learning and Artificial Intelligence. RL studies how animals and humans adapt to their environment by learning from experience which actions maximize reward acquisition [1]. Extant research has focused on the case learners receive veridical reward-feedback (e.g., true monetary earnings). However, as social creatures, much of the real-life feedback we receive is provided by others. Critically, such feedback may be misleading since others might manipulate us based on their own, even if well-intended, interests. For example, a friend might spare your feelings, expressing enthusiasm regarding you PhD proposal when in truth they find it superficial. Indeed, the prevalence of misinformation in our culture poses a pressing question: How do we adopt to environments where false and misleading feedback is provided?
The goal of this project is to unravel the learning processes governing such adaptation. Aim 1 is to develop novel RL behavioural tasks, in which participants receive reward-feedback (following choices) from various feedback-sources varying in reliability, i.e., the extent of misinformation they provide. Participants will also rate their beliefs regarding the reliability of feedback they receive. We will develop computational models for testing whether and how people learn which information sources are more or less reliable, and to what extent participants base subsequent choices on reliable feedback, while filtering out misinformation. Aim 2 is to test a hypothesis that deficits in aforementioned learning processes might relate to detrimental outcomes for social-communication and mental health such as political radicalisation, belief in conspiracy-theories, social anxiety and paranoia.
Aim 3 is to develop training protocols, based on our tasks, for increasing people’s sensitivity to feedback reliability, fostering an ability to ignore false feedback.This project promises a better understanding of the mechanisms governing adaptation in the presence of misinformation, how these affect social interaction and mental health, and interventions for keeping these detrimental influences at bay.
This studentship is open to students applying for China Scholarship Council funding. Queen Mary University of London has partnered with the China Scholarship Council (CSC) to offer a joint scholarship programme to enable Chinese students to study for a PhD programme at Queen Mary. Under the scheme, Queen Mary will provide scholarships to cover all tuition fees, whilst the CSC will provide living expenses for 4 years and one return flight ticket to successful applicants.
Applicants must be:
- Chinese students with a strong academic background.- Students holding a PR Chinese passport.- Either be resident in China at the time of application or studying overseas.- Students with prior experience of studying overseas (including in the UK) are eligible to apply. Chinese QMUL graduates/Masters’ students are therefore eligible for the scheme.
Please refer to the CSC website for full details on eligibility and conditions on the scholarship.
Applications are invited from outstanding candidates with or expecting to receive a first or upper-second class honours degree [and a masters degree] in an area relevant to the project such as Psychology, Cognitive Science, Economics, Mathematics, Statistics, Competer Sciences or Engineering. A masters degree is desirable, but not essential.
Prior Skills and Experience with running behavioural experiments, statistical analyses, computer programming, coputational methods and academic wriing are desirable.
Applicants from outside of the UK are required to provide evidence of their English language ability. Please see our English language requirements page for details: https://www.qmul.ac.uk/international-students/englishlanguagerequirements/postgraduateresearch/
Informal enquiries about the project can be sent to Rani Moran at r.moran@qmul.ac.uk. Formal applications must be submitted through our online form by 31st January 2023 for consideration, including a CV, personal statement and qualifications.
Shortlisted applicants will be invited for a formal interview by the project supervisor. Those who are successful in their application for our PhD programme will be issued with an offer letter which is conditional on securing a CSC scholarship along with academic conditions still required to meet our entry requirements.
Once applicants have obtained their offer letter from Queen Mary they should then apply to CSC for the scholarship by the advertised deadline with the support of the project supervisor.For September 2023 entry, applicants must complete the CSC application on the CSC website between 10th March - 31st March 2023. Only applicants who are successful in their application to CSC can be issued an unconditional offer and enrol on our PhD programme. For further information, please go to: https://www.qmul.ac.uk/scholarships/items/china-scholarship-council-scholarships.html
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[1]. Sutton, R. S., & Barto, A. G. (2018). Reinforcement learning: An introduction. MIT press.For Rani Moran’s publications see Rani's google shcolar page