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School of Biological and Behavioural Sciences

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  1. School of Biological and Behavioural Sciences
  2. Postgraduate
  3. PhD programmes
  4. Projects

Connected interactions in teaching and learning

Research environment

The School of Biological and Behavioural Sciences (SBBS) at Queen Mary is one of the UK’s elite research centres, according to the 2014 Research Excellence Framework (REF). We offer a multi-disciplinary research environment and have approximately 150 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.

The Psychology Department houses multiple human testing facilities, including equipment such EEG, TMS, eyetracking, Virtual Reality, as well as animal testing facilities. Dr Elisabetta Versace directs a research lab focusing on the foundations of knowledge and evolution of social behaviour. Dr Valdas Noreika leads a research program on the neural basis of cognition, inluding social interactions using dual electroencephalography (EEG) recordings. 

Training and development

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.

The PhD student will also be individually trained by lab members in developing coding, statistics, cognitive neuroscience and experimental psychology knowledge and skills.

Project description

Governments across the world are planning an increase in digital and remote health assessment, care and support. Moreover, education is increasing its demand for online student engagement and teaching. However, little is known on how to enhance and sustain remote social relationships. To address the needs of health and education and support the digital transition, we will investigate factors that can modulate and enhance engagement, learning and brain synchronisation between remote participants compared to in-person interactions.

The proposed project will build on current strengths in the labs: expertise in remote interactions, electroencephalography (EEG), hyperscanning, and automated behavioural tracking to make new discoveries on remote social interactions. The project will focus on: the role of imitation and verbal instructions in remote learning (Study 1); the role of one-to-one vs group remote interactions in learning and brain synchronisation (Study 2); the efficacy of different types of feedback for sustained engagement (Study 3).

The PhD student will carry out cognitive neuroscience experiments involving synchronized EEG measurement from two (private teaching) or more (group teaching) individuals situated either separately in adjacent rooms (remote learning) or in the same room (in person learning), and develop signal processing and machine learning tools. Aiming to identify factors that determine increased inter-brain synchronisation and successful learning online, we will manipulate facial expressions, gestures, informational complexity of slides and instructions, and the duration of presentation blocks.

Data analysis will involve programming in Matlab, Python and R, and using DeepLabCut/BONSAI closed loop AI feedback. Through digital technologies, AI and electrophysiological measures we will be able to provide evidence-based recommendations regarding the optimal conditions for the authentic interactions and efficient learning online.

Funding

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. 

Eligibility and applying

Applicants must:

  • Be Chinese students with a strong academic background.
  • Students must hold a PR Chinese passport.
  • Applicants can 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 in an area relevant to the project, e.g. psychology, computational neuroscience, data science. A masters degree is desirable, but not essential.

Applicants are required to provide evidence of their English language ability. Please see our English language requirements page for details.

The deadline for applications to Queen Mary is 30th January 2022. Applicants will need to complete an online application form by this date to be considered, 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 (as well as any 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 2022 entry, applicants must complete the CSC application on the CSC website between 10th March - 31st March 2022.

Only applicants who are successful in their application to CSC can be issued an unconditional offer and enrol on our PhD programme.

Apply Online

References

  • Josserand, M., Rosa-Salva, O., Versace, E., & Lemaire, B. S. (2021). Visual Field Analysis: a reliable method to score left-and right eye-use using automated tracking. Behavior Research Methods, https://doi.org/10.3758/s13428-021-01702-6

  • Noreika, V., Georgieva, S., Wass, S., & Leong, V. (2020). 14 challenges and their solutions for conducting social neuroscience and longitudinal EEG research with infants. Infant Behavior and Development, 58, 101393.

  • Santamaria, L., Noreika, V., Georgieva, S., Clackson, K., Wass, S., & Leong, V. (2020). Emotional valence modulates the topology of the parent-infant inter-brain network. NeuroImage, 207, 116341.

  • Slonina, Z., Bonzini, A. A., Brown, J., Wang, S., Farkhatdinov, I., Althoefer, K., ... & Versace, E. (2021, August). Using RoboChick to identify the behavioral features promoting social interactions. In 2021 IEEE International Conference on Development and Learning (ICDL) (pp. 1-6). IEEE.

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