I'm a bioinformatician working on epigenetics in glioblastoma multiforme at the Centre for Child Health and Genomics, Queen Mary University of London. Our project PI is Prof Silvia Marino, a neuropathologist whose research interests include the mechanisms controlling neural stem cell behaviour and how these are deregulated in tumour environments. As the senior computational researcher in an experimental group, I work with all the next generation sequencing data that is produced in the lab, including {m,mi,total}RNA sequencing, DNA methylation, whole genome sequencing and ChIP sequencing. I apply a variety of classification and clustering methods. My particular research interests are in the area of integrative statistical modelling, in which multiple sequencing modalities are combined to improve the statistical support of the inferences. I completed my D.Phil at the Centre for Mathematical Biology, University of Oxford, in early 2013. The topic of my doctoral research was bacterial motility, the fascinating means by which lone bacteria propel themselves through liquid media. Much of my work centred around a new, high-throughput microscopic tracking dataset that had become available. I developed a novel approach to analysing the tracks obtained and applied various mathematical modelling techniques to tackle challenging problems including: "what is the effect of the microscope camera sampling rate on the observed tracks?" and "does Rhodobacter sphaeroides reorientate lazily, by harnessing Brownian motion?". Previously, I have worked as a postdoc on the Crime, Policing & Citizenship (CPC; http://www.ucl.ac.uk/cpc) project at UCL, where I developed novel methods of predicting the future locations of urban crimes. I applied techniques from spatial and spatiotemporal analysis, statistics, machine learning and network theory. I was particularly proud of co-developing a new crime prediction method based around the urban street network. I also spent a year working as a data scientist in the risk team of a fintech startup.