PhD Studentship in Visual Cognitive Computational Neuroscience

Supervisor: Dr. Kamila Maria Jozwik, Jozwik lab

PhD fees status: Home fees only

(https://www.postgraduate.study.cam.ac.uk/finance/fees/what-my-fee-status), 4 years

Start date: October 2026 

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. We collect and analyse human behavioural and brain imaging (fMRI and M/EEG) data. We also analyse macaque electrophysiology data obtained through collaborations and perform cross-species comparisons. We 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: https://scholar.google.com/citations?hl=en&user=oEifmSgAAAAJ&view_op=list_works&sortby=pubdate). We also began exploring how to apply our expertise in visuo-semantic cognition and AI to neurotechnology and mental health applications. 

The PhD student 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', 'being animate', 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 PhD 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).

The ideal candidate will have:

• Extensive experience in programming in Python or Matlab and data analysis (essential, please note that coursework coding during an undergraduate or Master's degree will likely not be enough)
• Substantial research experience (essential, e.g., through research MPhil/Master's degree, or research assistant job)
• Experience with behavioural and neuroimaging (fMRI, M/EEG) data design/collection/analysis
• Experience in machine learning and AI
• A collaborative approach to doing science and willingness to help other lab members
• Curiosity and motivation to work on the proposed or related research questions.

Before applying, feel free to contact Kamila Maria Jozwik (Royal Society University Research Fellow and Assistant Research Professor, kamila.jozwik@mrc-cbu.cam.ac.uk). 

Lab research environment: MRC Cognition and Brain Sciences Unit with on-site 3T fMRI (with access to 7T fMRI), MEG, EEG, FUS and TMS. The Unit runs two MPhil Programs: Cognitive Neuroscience and NeuroAI, and PhD students may supervise MPhil students. The lab has links to international scientific ecosystems (e.g., the CBMM - now MIT Quest for Intelligence). The lab values commitment to rigorous, open science, supports diversity in all its meanings, and drives curiosity in a supportive, multidisciplinary, and international research environment.

Fixed-term: The funds for this post are available for 4 years in the first instance.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

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