George Bolt
I completed my PhD in 2023, under the supervision of Dr Simón Lunagómez (ITAM, Mexico; formerly Lancaster) and Professor Christopher Nemeth (Lancaster). My project was framed in collaboration with Elsevier, with a focus on the development of methodologies suitable to analyse online platform usage data. To this end, my research focussed on the development novel modelling frameworks to analyse a previously unexplored type of data structure that arises naturally when observing these user-platform interactions.
The decision to pursue a PhD, and particularly one at the STOR-i CDT, is one I am now very glad I took. The inclusive and inquisitive environment, the links with industry, and the great faculty at Lancaster, led to the development of skills and knowledge which I am sure will stick with me for the rest of my career.
Since leaving STOR-i, I have gone on to work as a Quantitative Analyst for Smartodds, where I develop models for predicting sporting outcomes.
Holly Jackson
I completed my PhD in 2023, supervised by Professor Thomas Jaki and Professor Andrew Titman and in collaboration with Quanticate, a clinical research organisation. The main focus of my PhD was novel, efficient, and adaptive methodologies for the design of clinical trials. Taking a new drug from discovery to market is a lengthy and costly process, the use of more efficient trial designs in the form of adaptive clinical trials could greatly reduce the time and cost of this process.
I enjoyed my time at the STOR-i CDT, I particularly benefitted from the cohort structure which facilitated collaboration across different statistical and operational research disciplines and gave me a great sense of community and support through those difficult PhD moments. In addition to the industry exposure at STOR-i, I participated in the Roche Internships for Scientific Exchange in the Department of Neuroscience and Rare Diseases for 12 months. This extra industry experience introduced me to cross-discipline working as well as specific medical statistical methodologies.
Since leaving STOR-i, I now work as a postdoctoral researcher at Hôpitaux Universitaires de Genève in Switzerland in collaboration with ECR91快活林D, where I support the design and analysis of perpetual observational studies and continue my research on novel efficient clinical trial designs.
Graham Laidler
Concluding in 2023 under the supervision of Barry Nelson (Northwestern University), Lucy Morgan, and Nicos Pavlidis (both Lancaster), my PhD research combined machine learning methods with the data and theory of stochastic simulation. At STOR-i, I benefited from the exposure to a wide range of topics across the spectrum of statistics and operational research, and now work as a statistical analyst for global wildlife trade at TRAFFIC, a conservation programme based in Cambridge.
Callum Murphy-Barltrop
I completed my PhD in 2023, supervised by Dr Jennifer Wadsworth and Dr Emma Eastoe. The focal point of my PhD, supported by funding from the UK's Office for Nuclear Regulation, centred on the domain of statistics known as extreme value theory. In practical terms, this domain holds enormous significance as it equips us with tools for evaluating risks stemming from natural hazards, such as floods, storms and heatwaves - events whose occurrence has grown more frequent due to the impact of climate change. My research focused on developing novel techniques for estimating and modelling extreme risks across multiple hazards simultaneously. Additionally, I also developed a methodology for modelling climate trends in the extreme setting.
I am incredibly grateful to have completed my PhD at the STOR-i CDT. The quality of research and expertise within the CDT, combined with the sense of community and strong industry connections, made STOR-i an ideal research environment for me. Being part of STOR-i also enabled me to develop a wide range of skill sets, both personal and professional, that have been massively beneficial in my career as a young researcher.
Since leaving STOR-i, I now work as a postdoctoral researcher at Technische Universität Dresden in Germany, where I continue to do research in extreme value theory.
Srshti Putcha
I completed my PhD at the end of 2023, supervised by Professor Paul Fearnhead and Professor Chris Nemeth. The main focus of my research was to develop scalable Bayesian inference for big data, specifically for the class of stochastic gradient Markov chain Monte Carlo samplers.
I have been working in the consumer finance sector for just over three years. I currently work at Capital One as a Senior Data Scientist. My team works to support the UK business’ customer acquisition credit risk model. Prior to my current role, I worked at the UK&I Experian DataLabs in London.
Alongside work, I am actively involved in the Royal Statistical Society and I am currently a member of the Council.
Jess Spearing
I completed my PhD in 2023, supervised by Jonathan Tawn, Tim Paulden, David Irons and Grace Bennett (ATASS Sports). My PhD centred on the field of statistical ranking systems, and utilised methodology in the areas of extreme value theory, paired comparison, Bayesian inference, and longitudinal data analysis. These methodological developments were primarily demonstrated on sports data, although kept general throughout.
Particularly upon starting the PhD, I greatly benefitted from my cohort structure, from the social aspects more broadly, and from the sense of community, which made for a welcoming atmosphere. In addition to the crucial industry exposure at STOR-i, e.g., problem-solving days, I also took a year-long internship opportunity working at the Behavioural Neuroscience Lab at Roche, Basel. As well as the technical statistical skills I learnt here, I picked up further industry experience, such as collaborative coding, and working cross-discipline with experts from other fields.
I now work as a statistician for Shell's Decision Science department in Amsterdam, NL.