Project Title: Enhancing prediction of the effects of genetic variation on DNA methylation using machine learning
Supervisor: Dr Nathan Skene
Location: Level 7, Sir Michael Uren Hub, White City Campus, 86 Wood Lane, W12 0BZ
About Me
I am a Clinical Medicine Research student and President’s PhD scholar in the Skene group in the UKDRI at Imperial. Initially specialising in biochemistry during my undergraduate degree at the University of Cambridge, I gained experience applying machine learning and statistics to biological problems during my master’s.
Following a master’s project predicting single-cell gene perturbations with foundation models in Dr Bornelöv’s group, I continued to work as a research assistant in the group. Here, I focused on training language models on eukaryotic coding sequences, aiming to understand the complex mechanisms of codon-dependent gene regulation across species.
During my PhD, I aim to enhance machine learning models’ ability to capture individual genetic variation, particularly for predicting DNA methylation patterns. These improved models could then be used to better identify causal genetic variants underlying neurodegenerative diseases.
Outside the lab, I enjoy playing and watching football, tennis and base.
Qualifications
2020-24: MSci Natural Sciences (Systems Biology), University of Cambridge
Research Interests
• Training and scaling machine learning models.
• Deep learning approaches for epigenomic prediction.
• Methods for predicting the effects of genetic variants.
Contact Details
Email: toby.clark25@imperial.ac.uk LinkedIn: toby-clark-r4
