Application of Geometric, Topological and Artificial Intelligence Techniques for the Analysis of Three-dimensional Cells Observed with Electron Microscopy at City, University of London

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Qualification Type: PhD

Location: London

Funding for: All applicants (UK, EU and International)

Funding amount:

Tax-free stipend of £21,000/year and 50% Tuition fees (Home/EU/International)

Hours: Full Time

Closes: 30 November 2023

Applications are invited for a PhD studentship in the Department of Computer Science at City, University of London in collaboration with experts in Microscopy and Biology from the Francis Crick Institute.  The successful candidate will have the opportunity to work on an exciting interdisciplinary project in the application of Geometric, Topological and Artificial Intelligence techniques for the analysis of three-dimensional cells observed with Electron Microscopy.


Traditional approaches in computer vision and image analysis (such as unsupervised traditional algorithms and, more recently, deep learning methodologies) do not fully incorporate the geometric and topological properties of the anatomical or biological structures contained within the data. Observation of samples with electron microscopy has grown considerably and now it is possible to obtain 3D datasets with excellent resolution and contrast, but which require sophisticated analysis methodologies.

This PhD will investigate the incorporation of image processing and deep learning methodologies with topological data analysis and geometry processing techniques to achieve in-depth analysis of high-resolution biomedical images. The project will be a collaboration between the School of Science and Technology at City, University of London where the student will be based, with the Francis Crick Institute.

Eligibility and requirements 

The candidate should hold a good honours degree (no less than a second-class honours degree or an equivalent qualification) in an appropriate subject (including mathematics, physics, computer science, engineering). A master’s degree in a related area would be an advantage.

They should demonstrate aptitude for original research, have a very good mathematical background and very good programming skills (e.g., Python, Matlab). They should also have a good background in areas such as machine learning (e.g., deep learning), geometry processing, image processing, computer vision, and TDA.

Knowledge of microscopy or biology is not necessary but would be advantageous.

Scholarship: an annual, tax-free stipend of £21,000 (for three years). 50%  tuition fees for Home/EU/International.

An extra £1,500/year salary supplement will be offered to all successful candidates from underrepresented communities. In particular, the stipend supplement will be reserved for female, LGBTQ+ and disabled applicants.

Each student may also have the opportunity to earn around £2,200/year on an average (max. is around £4,300/year) through a teaching assistantship.

For informal inquiries, contact:

Panos Giannopoulos (pa****************@ci**.uk) or

Carlos Reyes-Aldasoro (co*******************************@ci**.uk).

How to apply

Online applications should be submitted by clicking the ‘Apply’ button.

For queries regarding the application process, please contact pg*************@ci**.uk

City, University of London is committed to promoting equality, diversity and inclusion in all its activities, processes, and culture for our whole community, including staff, students and visitors.

We welcome applications regardless of age, caring responsibilities, disability, gender identity, gender reassignment, marital status, nationality, pregnancy, race and ethnic origin, religion and belief, sex, sexual orientation and socio-economic background. City operates a guaranteed interview scheme for disabled applicants. 

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