Supervisor: Dr. Kamila Maria Jozwik, Jozwik lab, University of Cambridge
Application deadline: 2 April 2026
Application link: https://www.cam.ac.uk/jobs/postdoctoral-research-associate-fixed-term-su49028
Start date: October 2026 (there is some flexibility)
The Jozwik lab studies visuo-semantic cognition combining cognitive science, neuroscience, and computational modelling. The lab’s research has focused on probing specific visual dimensions in the context of face, animacy, and object representations more generally. They collect and analyse human behavioural and brain imaging (fMRI and M/EEG) data. They also analyse macaque electrophysiology data obtained through collaborations and perform cross-species comparisons. They use machine learning techniques for neural data analysis and computational modelling with a special interest in biologically-inspired deep learning and AI models (NeuroAI). The computational models we work with include vision deep learning models (including topographical, recurrent, or developmentally inspired models), multimodal vision and language models, and Large Language Models. Please find prior work here: Google Scholar. They also began exploring how to apply our expertise in visuo-semantic cognition and AI to neurotechnology (Focused Ultrasound Stimulation) and understanding mental health conditions.
The postdoctoral researcher is welcome to work on one (or more) of the three aspects of the research programme funded by the Royal Society that aims to disentangle and model behaviourally-relevant visual and semantic dimensions (characteristics of objects: ”curved”, ”pink”, ”having eyes”, “being animate”, ”having agency”, or ones that are hard to name) of visual cognition in the human brain, while increasing the ecological validity of experiments (including mobile EEG and immersive technologies), in the light of the below three aims. Note Dr Jozwik would be happy to discuss projects related to these aims, as there is some flexibility in research directions.
1) characterise behaviourally-relevant visual and semantic dimensions by the use of large-scale brain
imaging datasets of responses to images and model these representations with computational models and
validate these predictions in follow-up neuroimaging experiments,
2) define and model dimensions related to the perception of animacy when interacting with objects and people
using videos (behaviour, fMRI, and MEG),
3) determine to what extent these brain representations and dimensions change when humans are immersed
in the environment (VR/AR and/or mobile EEG).
Posted on 12/03/2026
