CV

Education

PhD Biological Sciences, Queen Mary University of London (2022-current)
- Bayesian Inference and Deep Learning approaches to infer patterns of disease spread from the genomes of the malaria parasite
- Supervisors – Prof Richard Nichols, Dr Matteo Fumagalli, Dr Robert Verity, Prof Alexander Gnedin
MSc Bioinformatics, Queen Mary University of London (2021-2022)
- Distinction
BSc(Hons) Natural Sciences Biochemistry Major Chemistry Minor, University of Bath (2018-2021)
- 2.1
Heston Community School (2011-2018)
- A level: Biology A, Chemistry A, Mathematics A, Further Mathematics (AS) A
- GCSE: 3 As, 6 As, BCS level 2 ECDL Certificate in IT Application skills Distinction

Brunel University London - Computational Biology Internship
- JUNE 2021 – SEPTEMBER 2021
- Learning Visual Molecular Dynamics (VMD) through monthly meetings and online tutorials, with the support of Dr Sarath Dantu. With the foundations, I explored PETases and CUTinases and compared the residues present which facilitate catalytic activity. Using trajectories, I could alter the protein to display areas of high movement and thus producing high quality graphics
University of Bath - Bioimaging Internship
- JUNE 2020 – SEPTEMBER 2020
- Working as an undergraduate researcher I investigated the ROCK signaling pathway. I expanded my knowledge of bioimaging software’s such as Ilastik and ImageJ. I analysed cells at different stages of the cell cycle and identified the effects of the ROCK inhibitor Y-27. Using the outputs from Ilastik, I used R to present my findings to the team in weekly meetings. Eager to expand my knowledge on Bioimaging I continued this research in my final year project.