Do you want to contribute to an understanding of the interaction between memory and language? In this two-year postdoctoral position, you will join the ERC-funded project
Memory access in language (MEMLANG): How we store and retrieve linguistic information, led by Jakub Dotlacil, at the Institute for Language Sciences (ILS), Utrecht University. Together with an interdisciplinary team, you will investigate how linguistic information is represented, accessed and modelled.
Your jobThe project aims to develop, implement and test a general model of memory that provides insight into how linguistic information is stored and retrieved, and how language use is intertwined with memory during communication. The model will be hybrid, merging linguistic factors uncovered in computational and theoretical linguistics with general cognitive mechanisms. The overarching goal is to determine how memory mechanisms can be generalised across linguistic domains, from the lexicon through syntax to discourse semantics, and how plausible memory models can predict diverse quantitative data in linguistics and cognitive science.
The project has two components: an empirical one and a computational one. The empirical strand develops and analyses behavioural experiments (reaction times, eye fixations) and EEG data. The computational strand simulates behavioural and neural data related to processing and memory retrieval.
As a postdoctoral researcher, you will be part of the computational component of the project. You will collaborate closely with the principal investigator, two PhD candidates (working in psycholinguistics and cognitive science) and one postdoctoral researcher (working on NLP, with a focus on multimodal models combining vision and language).
Your research will focus on developing, implementing and testing a general model of memory that explains how linguistic information is stored and retrieved, and how language use and memory processes interact during communication. The computational model will integrate insights from computational and theoretical linguistics with general cognitive mechanisms, with the goal of predicting behavioural and neural data across linguistic domains, from the lexicon through syntax to discourse.
Your main tasks will include:
- data modelling and analysis, in particular modelling behavioural (reading-time) and EEG data by combining NLP techniques with theoretical insights from underlying cognitive processes and computational cognitive modelling;
- reporting findings in peer-reviewed journals and at international conferences;
- contributing to the supervision of PhD candidates within the team.