Imperial College London
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1 week ago
Fully Funded PhD in Neural Manifolds, Memory and Cognitive Change in Dementia Imperial College London in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Fully funded UK PhD studentship for 3.5 years with a stipend of £23,805 per annum.
Deadline
Oct 31, 2026
Country
United Kingdom
University
Imperial College London

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About this position
Fully funded 3.5-year PhD studentship at Imperial College London in the Department of Bioengineering, working on neural manifolds, memory, cognitive change, and dementia. The project is supervised by Prof. Simon Schultz (Imperial College London) and co-supervised by Dr JeYoung Jung (University of Nottingham), with collaborative visits to Nottingham.
The successful candidate will adapt neural manifold techniques developed in animal models to human neuroimaging data to study how memory-related brain activity changes with healthy ageing and in dementia. The work sits at the interface of computational neuroscience, bioengineering, cognitive neuroscience, and clinical research, and may involve fMRI data from PREVENT and potentially magnetic resonance spectroscopy data.
Applicants should have a strong quantitative background in engineering, computer science, physics, mathematics, or a related discipline, plus strong programming and computational analysis skills. Interest in neuroimaging analysis is preferred, and prior exposure to neuroscience is helpful. Experience with dimensionality reduction, machine learning, or population-level neural data analysis in Python or MATLAB would be an advantage.
Funding is fully covered for UK students, with a stipend of £23,805 per year for 3.5 years. The application deadline is 31 October 2026, and the start date is from 1 January 2027.
To apply, email Prof. Schultz with a CV, a brief cover letter describing your motivation, and transcripts. References will be requested from shortlisted applicants.
Funding details
Fully funded UK PhD studentship for 3.5 years with a stipend of £23,805 per annum.
What's required
Applicants should have a strong background at BSc/MSc/MEng or equivalent level in engineering, computer science, physics, mathematics, or another computational/quantitative discipline. Strong programming and quantitative/computational analysis skills are required. Interest in human neuroimaging data analysis (e.g. fMRI, EEG, or MEG) is preferred, along with some prior knowledge of neuroscience. Experience with dimensionality reduction, machine learning, or population-level neural data analysis in Python or MATLAB would be an advantage.
How to apply
Email Prof. Simon Schultz with your CV, a brief cover letter explaining your motivation, and transcripts. References will be requested from shortlisted applicants.
More information can be found here
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