Curious about cancer.
Stubborn about evidence.
A short version of what I do, how I got here, and what I bring to a collaboration.
I'm a PhD researcher studying how tumours organise themselves — and how to read those signals from a blood draw.
Based at Swansea University Medical School, my work sits between wet-lab biology and computational analysis. The thread running through everything is the same question: which cells in a tumour are doing what, and what does that tell us about how to treat the patient.
Outside of the lab I run BioOps — an open library of step-by-step research protocols — because some of the most useful knowledge in science still lives in notebooks rather than papers.
The path here.
2023 – Present
PhD, Biomedical Sciences
Swansea University Medical School
Translational cancer research with the Cancer Microenvironment Group — focusing on the spatial biology of triple-negative breast cancer and liquid-biopsy biomarker discovery.
2021 – 2023
MSc, Cancer Biology (Distinction)
University of Cambridge
MRes thesis on tumour-immune crosstalk in pancreatic cancer organoids, supervised at the CRUK Cambridge Institute.
2018 – 2021
BSc (Hons), Biomedical Sciences
University of Manchester
First-class honours; final-year project on CRISPR screening for synthetic-lethal targets in BRCA-mutant cell lines.
2020
Cancer Research UK Summer Studentship
Manchester Institute
Independently characterised a panel of EGFR-mutant NSCLC organoids; co-author on a follow-up methods paper.
How the work gets done.
Wet lab
- Cell culture (2D, 3D, organoids)
- Multiplex flow cytometry
- CRISPR/Cas9 perturbations
- Western blot · qPCR · ELISA
- CODEX & confocal imaging
- Library prep (RNA-seq, ATAC-seq, MeDIP)
Dry lab
- R (tidyverse, Bioconductor, Seurat)
- Python (scanpy, scikit-learn, PyTorch)
- Nextflow & Snakemake pipelines
- Spatial analysis (Visium, CODEX)
- Statistical modelling
- Reproducible research with Git + Quarto
Soft skills
- Cross-disciplinary collaboration
- Patient-facing study coordination
- Conference presenting
- Manuscript writing
- Undergraduate supervision
- Public engagement
Values that shape the science.
Rigorous, then fast
I'd rather publish a smaller, fully reproducible result than a flashy one with cracks underneath.
Open by default
Code, protocols and (where ethics allow) raw data are shared — science compounds faster when others can build on it.
Patient-centred
Every cohort I work with represents a person who chose to contribute their data. That trust shapes every decision.
Mentorship matters
I supervise undergraduates and MSc students; their questions sharpen mine, and their careers shape the field.