Research Associate

We are seeking a highly motivated Postdoctoral Researcher to work with Professor Kim Plunkett to develop a neural network model of the infant bilingual lexicon. This model may build on a monolingual base model already developed by the PI in the Oxford Babylab. The purpose of the modelling endeavour is to mimic aspects of infant behaviour in experimental settings, in particular, the inter-modal preferential looking task.

The post is full time, fixed term for 13 months or until 31 December 2023 depending on the start date.

You will be responsible for code development, stimulus creation and simulating neural network models of infant bilingual development, requiring a working knowledge of Python and experience with artificial neural network models.  As well as running the simulations you will analyse the results and write up manuscripts for submission to international academic journals.

Applicants should hold a PhD/DPhil, or be near completion, in a relevant subject along with the ability to work independently and collaboratively.  As well as the ability to write technical documents, troubleshoot programming problems, some knowledge of Graphical Processing Units (GPUs) and their use in the context of neural network modelling is essential.

The closing date for applications is midday on 24th October 2022.  It is anticipated that interviews will be held on 2nd November 2022.

You will be required to upload a covering letter explaining how you meet the job requirements, as well as a CV and details of two referees as part of your online application.

To apply for this role and for further details, including the job description and selection criteria, please see the links below.