Research Associate in Topological Data Analysis for Cell Biology (10407)
Rosalind Franklin Institute
This is an exciting research opportunity to join the VirtuAI Cell project which aims to develop a virtual mapping of intracellular contents of biological cells. This leads to the ultimate goal of running in-silico cell simulations that use such mappings to model how the dynamics of intracellular contents may modulate in response to various types of cell disturbances; e.g., due to the injection of a drug molecule; or the intracellular growth of cancer promoting mutations, the checking of which one could model to predict new routes towards preventative cancer.
The Research Associate will develop and apply persistent homology to automatically classify cellular structure in experimental 2-D microscopy and 3-D tomography data, to help build a virtual mapping of biological cells. The role-holder will use persistent homology to represent and classify biomedical structure and explore how such structural representations can track over multi-scale image resolutions. The work may also involve applying topological data analysis (TDA) to assist with the design, construction and deployment of new feature engineering and optimisation strategies for the machine-learning (ML) modelling of cellular data. More generally, this role offers a great opportunity for an expert in persistent homology to become a valued member of a highly interdisciplinary, challenge-focused project team that aims to solve a global research challenge.
As a Research Associate at the Franklin, you will bring scientific knowledge and skills to deliver a specific research project and/or you will bring independent, creative science, or specific skills to a team delivering a project or program. Through this work, you will build scientific independence, develop new science and leadership skills, and establish a growing reputation externally.
Key Responsibilities
As a Research Associate, you will:
- Employ persistent homology to represent and classify structures in cell biology, using experimental data from 2-D microscopy images and 3-D tomograms
- Analyse and interpret results from persistent homology in liaison with experts in cell biology
- Apply persistent homology to track structural representations of biocellular species over multi-scale image resolutions
- Use persistent homology to track structural representations of biocellular species over time
- Curate large volumes of simulated data to help develop persistent homology for cell biology
- Apply TDA to assist ML modellers with the feature engineering and optimisation of cellular data
- Create data representations using TDA to help make more efficient ML models for cell biology
- Perform or supervise data annotation for training and evaluation purposes where necessary
- Plan data acquisitions with experimentalists who conduct them, analyse and interpret results and supervise delivery of outputs (e.g. research report, patent application) in a scientific/technology area of interest.
- Work within a project team, contributing to wider projects around key Challenges.
- Lead major contributions to outputs from research including papers, patents and both internal and external presentations.
- Support and develop others including day-to-day supervision of students or visitors in areas related to own research.
- Have supervised, staged progression to first stages of scientific independence with opportunities to further develop science and skills/experience.
- Enhance your research through collaboration with other researchers and make active contributions to exchanging ideas through your own network.
- Be able to understand, interpret, create and communicate appropriately within a research context.
- Develop search and discovery skills and techniques.
- Be supervised by a Scientist/Senior Scientist in delivery of research outputs, either in the context of a project or Challenge or as an early career development fellow.
Before submitting your application, please ensure you read the Job Information Pack for full details of this role on our website.
This job description sets out the skills and experiences we believe are needed to be able to do this job but, research also tells us women are much more likely than men to take this list of requirements as absolute and self-select out of the process. If you think you can deliver this role then we want to hear from you, regardless of the boxes you did not tick.
Whilst the role requires candidates to hold a PhD/DPhil (or equivalent), we may consider candidates who have submitted their PhD/DPhil thesis, in which case the initial appointment will be made at £38,500 per annum (to be increased on completion of the PhD/DPhil qualification).
The Franklin’s underlying aim is to produce the best science for research today, and this means resolutely embracing a diverse team, who have a wide range of experiences, skills and knowledge to push forward on the innovative work our institution delivers. Both our work and our institution are better for it. For further information, view our Equality, Diversity and Inclusion Policy.
We are committed to creating an inclusive environment where every applicant has an equal opportunity to showcase their talents and abilities. This includes making adjustments for candidates with specific needs. Please contact us at recruitment@rfi.ac.uk to discuss your requirements confidentially.
At the Rosalind Franklin Institute we also welcome applications from all around the world!
How to Apply
To be considered for this role, please upload a CV and cover letter explaining why you think you are the right person for this job. The link to apply is provided via the ‘Apply’ button above.
Closing date: The closing date for applications is 23:59 on Sunday 30th August 2026.
