About the Project
A fully funded position is available to study full-time for a PhD registered at UCL. This work is funded by an Alzheimer's Research UK PhD Scholarship. This PhD will determine when Aβ pathology predicts dementia, and how this is modified by co-pathology, vascular disease and genetics. It will define Aβ spatial phenotypes across neurodegenerative diseases to improve biomarker interpretation and patient stratification.
The student will work with approximately 1,500 post-mortem cases held at the Queen Square Brain Bank (QSBB), spanning Alzheimer's disease, neurologically normal ageing and a range of other neurodegenerative disorders. Using established digital pathology pipelines, they will generate quantitative regional measures of Aβ alongside co-existing pathologies, integrate these with clinical and genomic data (including APOE genotype), and apply computational modelling to define reproducible Aβ spatial phenotypes and inferred patterns of regional progression. The student will also contribute to methodological development in quantitative image analysis and AI-assisted extraction of structured data from clinical and neuropathology records.
Person specification
Essential criteria
- Master's degree in a relevant discipline (e.g. neuroscience, pathology, computational biology), in addition to a bachelor's degree (2:1 or higher) or international equivalent.
- Practical experience of quantitative image analysis of human postmortem tissue sections, e.g. whole-slide immunohistochemistry or multiplex immunofluorescence imaging.
- Hands-on experience with digital pathology platforms (e.g. QuPath), including training AI models for region and cell segmentation and downstream analysis.
- Practical experience with histology slide digitisation.
- Experience working between clinical and research-based teams, and familiarity with governance for human tissue and clinical data.
- Working proficiency in at least one programming environment (e.g. Python, R), and IT proficiency at advanced user level (MS Office suite, web-based systems, databases, file management).
- Ability to critically interpret data and synthesise complex ideas, with attention to detail in record-keeping and in spotting data inconsistencies.
- Excellent research and project management skills: proactive and driven, with strong problem-solving ability, the capacity to act on own initiative, good time management under the pressure of deadlines and competing priorities, and an understanding of when to refer queries or concerns to the supervisory team.
- Excellent written communication skills and numeracy, with an early track record of scientific writing (dissertation, report, preprint or publication), ready to adapt to the demands of writing a PhD thesis.
- Excellent oral communication skills with proven ability to deliver research presentations to technical audiences.
- Good interpersonal skills with the ability to work co-operatively in a multidisciplinary setting, and a genuine interest in research with a commitment to supporting high-quality research.
Desirable criteria
- A primary medical or clinical qualification, and/or a background in neuroscience.
- Experience with quantitative modelling approaches such as regression and mixed-effects models, dimensionality reduction or machine learning, and with integrating imaging-derived data with clinical and genetic datasets.
- Interest in public engagement and outreach, including communicating post-mortem and AI-based research to patient and public involvement groups and donor families.
Application process
Deadline: 23:59 BST, 28/08/2026
Please submit applications to z.jaunmuktane@ucl.ac.uk in the following format:
- A CV or biographical sketch (2 pages maximum)
- Personal statement (300 words maximum) outlining (i) why you are applying for this project, (ii) what makes you the ideal candidate, (iii) what training experience you have had to date.
- Name and contact details for at least one person who could be approached as a referee.
Only shortlisted candidates will be notified. For further information contact Associate Professor Zane Jaunmuktane, z.jaunmuktane@ucl.ac.uk
Funding Notes
Funded PhD Project: This project is funded by an Alzheimer's Research UK PhD Scholarship for 3.0 years full-time, with a proposed start date of 1 February 2027. The award covers tuition fees at UK resident students, though the amount may depend on your nationality. Non-UK students may still be able to apply and a stipend at UKRI rate of 23,805 per year including London allowance. Successful applicants must hold, or be able to obtain, immigration permission covering study in the UK for the duration of the programme.
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