[Manchester-Melbourne Dual Award] Identifying drivers of language development in children’s interactions

Language skills are vital to children’s ability to thrive in school and elsewhere. In order to support children’s language development we need to understand the aspects of early interaction that drive their learning (Donnellan et al, 2019; Down et al, 2015). The goal of this PhD project is to use statistical analysis of observational data to identify these. The student will oversee the collection of a) home videos of children interacting with their caregivers at 24 months of age b) videos of the same children interacting with preschool educators at 24 months and c) home videos of child language during play at 30 months. Supported by expert training, they will code the videos for language and communication. Recent work by the supervisory team used statistical analysis to identify the combinations of child and caregiver behaviours in videos collected at 12 months of age that are the best predictors of language development in the second year of life (Donnellan et al, 2019). The current project will extend this to interactions during the third year – identifying the behaviours in the 24-month recordings that predict language ability at 30 months.

Analysis of the behavioural data will involve the use of time-series modelling. To date, all work in this area has built statistical models based on counts of behaviours identified across videos. This required the researcher to decide in advance what combinations of behaviours to count, constrained by the need to avoid a combinatorial explosion. The current work will analyse the video transcriptions directly – treating them as behaviours unfolding across time and using neural time series models to identify sequences of behaviours that are associated with later language ability. The student will attend courses on the MSc in Computational and Corpus Linguistics at the University of Manchester to acquire skills where necessary.

Eligibility

This is an interdisciplinary project spanning Linguistics, Psychology, Education, Computer Science and Statistics. We welcome applications from students with backgrounds in any relevant area, and training in other component areas will be available where needed. Please note that the successful candidate will spend 12 months of their PhD at the University of Melbourne, Australia and the remainder at the University of Manchester in the UK.

Academic

• Bachelor’s (Honours) degree at 2:1 or above (or overseas equivalent); and
• Master’s degree in a relevant subject – with an overall average of 65% or above, a minimum mark of 65% in your dissertation and no mark below 55% (or overseas equivalent)

English Language

All applicants must provide evidence of English language proficiency:

• IELTS test minimum score – 7.0 overall, 7.0 in writing.
• TOEFL (internet based) test minimum score – 100 overall, 25 in all sections.
• Pearson Test of English (PTE) UKVI/SELT or PTE Academic minimum score – 76 overall, 76 in writing.
• To demonstrate that you have taken an undergraduate or postgraduate degree in a majority English speaking nation within the last 5 years.
• Other tests may be considered.

How to apply

The application deadline will be Midnight (GMT) on 14/03/25. Apply online for PhD Linguistics at the University of Manchester.

Under Section 6 Research Details select ‘Yes’ to ‘Are you applying for an advertised project?’. Insert the project title as stated at the top of the advert. It is recommended when entering the name of the supervisor to simply enter this and not use the supervisor search function.

Please indicate in Section 9 Funding Sources your intention to apply for the Manchester-Melbourne Studentship.

Please ensure all required supporting documents are included at the time of submission, as incomplete applications may not be considered. Your application must include the following:

• A copy of your Bachelor’s academic transcript and certificate.
• A copy of your Master’s academic transcript and certificate. If your Master’s degree is pending, please provide an interim transcript.
• If you have completed more than one Bachelor’s or Master’s degree, please provide evidence for each. If your transcripts are in a language other than English, you must provide an official English translation. If your weighted average mark or GPA is not included on these documents, please also include an official document from your university verifying this information.
• An academic CV, summarising your employment history, publications and highlighting experience demonstrating your research potential.
• Supporting statement of a maximum of 700 words indicating why you would like to undertake this studentship and explaining how your focus, experience, and skills link to the research outlined above
• Example of a piece of academic writing produced by you of up to 5,000 words (you may consider submitting two shorter pieces if these deal separately with conceptual and empirical analyses). This may be an academic essay or chapter(s) from a dissertation, in which case, an abstract or introduction outlining the context/aims/research questions of the study must also be included.
• You must nominate two academic referees (including one from your most recent institution). Your referees will be contacted directly via the Referee Portal following the submission of your application form. You may wish to contact your referees to request they submit your reference in a reasonable timeframe as this forms part of the review process;
• A PhD Proposal is not required.

Formal interviews: Interviews are expected to take place in April 2025.

If you have any questions or would like to discuss this further, please contact Dr Colin Bannard (colin.bannard@manchester.ac.uk)

Equality, diversity and inclusion

Equality, diversity and inclusion are fundamental to the success of The University of Manchester, and are at the heart of all of our activities. We know that diversity strengthens our research community, leading to enhanced research creativity, productivity and quality, and societal and economic impact.

We actively encourage applicants from diverse career paths and backgrounds and from all sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation and transgender status.