AI-guided neuroscientific approach to understand learning difficulties
The objective of this studentship is to combine artificial intelligence and neuroscientific approaches to better understand the neurocognitive mechanisms of mathematics learning and development in children with dyslexia.
Start date1 October 2022
Funding sourceEPSRC Doctoral Training Partnership
Enhanced EPSRC stipend (£19,062 per annum for 2022-23, with annual increments based on inflation) and fees covered. Funding also includes a research training and support grant of £3,000 for the duration of the studentship
We invite enthusiastic applicants for a full-funded PhD studentship in Psychology sponsored by the EPSRC. This exciting 3.5 years programme, supervised by Dr Mojtaba Solatnlou and Dr Debbie Gooch in collaboration with the AI-Centre at the University of Surrey.
Learning difficulties (for example, dyslexia) are one of the most prevalent neurodevelopmental disorders affecting individuals’ academic achievement and broader life outcomes, with consequences for the individual and societies. The objective of this project is to combine artificial intelligence and neuroscientific approaches to better understand the neurocognitive mechanisms of mathematics learning and development in children with dyslexia. This will be achieved through a longitudinal study in which we will examine changes in behavioural and brain responses of individuals with and without dyslexia during mathematics and language processing tasks using simultaneous functional Near-Infrared Spectroscopy (fNIRS) and EEG and apply classification and multi-variate pattern analyses (MVPA). Furthermore, a training study will be used to look at how specific training in calculation skills effects behaviour and neural processes.
The PhD student will receive training in neuroscientific methods, signal processing and modelling. This studentship will allow an opportunity to work in a multidisciplinary team that includes cognitive psychologists, cognitive neuroscientists, computer scientists, and data scientists, in a supportive environment. We are looking for a candidate with a background in cognitive neuroscience, cognitive science, psychology, computer science, or other relevant fields. Previous experience in using EEG, fNIRS, artificial intelligence, classification, multivariate pattern analysis, statistics, modelling, effective written and oral communication skills, and a passion to learn and impact society is advantageous. For enquiries, please contact Dr Mojtaba Soltanlou (email@example.com).
The University of Surrey and our collaborative partners provide a vibrant, interdisciplinary research environment, with access to state-of-the-art facilities. We see our postgraduate researchers as an integral part of our research community, collaborating and innovating together with academics at all levels. We want the most talented researchers from diverse backgrounds to join us, bringing new ideas and perspectives. We will help you make the most of your potential, removing barriers where we can and supporting you with dedicated career guidance. We offer generous funding packages, sector-leading researcher development training and mentoring, and dedicated employability support.
Whatever your aspirations, Surrey is where research careers are launched and nurtured.
Related linksThe Mathematical Cognition and Learning Society The Society for functional Near Infrared Spectroscopy
- Andreu-Perez, J., et al. (2021). Explainable artificial intelligence-based analysis for interpreting infant fNIRS data in developmental cognitive neuroscience. Communications biology, 4(1), 1-13.
- Soltanlou, M., et al. (2022). Training-related activation increase in the parietal cortex in children with developmental dyscalculia: An fNIRS study. Brain Structure and Function.
- Soltanlou, M., et al. (2018). Reduction but not shift in brain activation in arithmetic learning in children: A simultaneous fNIRS-EEG study. Scientific Reports. 8(1), 1707.
- von Lühmann, A., et al. (2020). Using the general linear model to improve performance in fNIRS single trial analysis and classification: a perspective. Frontiers in human neuroscience, 30.
Applicants are expected to hold a minimum of an upper second-class honour’s degree (65 per cent or above) in psychology (or a related discipline) and a master’s degree in a relevant subject with a pass of 65 per cent or above.
English language requirements
IELTS Academic: 6.5 or above (or equivalent) with 6 in each individual category.
How to apply
Applications should be submitted via the Psychology PhD programme page on the "Apply" tab (select October 2022 start date). Please clearly state the studentship title and supervisor on your application. Once you have completed and submitted your application, please send an email to the primary supervisors confirming you have applied.