I joined thinking I wanted to do one type of PhD but ended up doing a completely different one due to the flexibility that was provided in finding/forming a PhD during the masters year
Prior to joining SAMBa I did my MMath at the University of Exeter and graduated in 2017, with a few summer projects with UKHSA.
I completed my MRes+PhD with Prof McGrogan and Prof Bartlett in 2022, investigating the possible causal impact of Systemic Sclerosis on cancer, with an emphasis on prevalent cohorts (left-truncated data). From this I have a background in epidemiology, medical statistics and general statistical methodology. Over the course of my studies, I attended 5 ITTs with projects including with the Environment Agency, Willis Towers Watson and the Paraguayan government finance department.
The SAMBa environment, and the CDT structure as a whole, was greatly beneficial. The masters gave me a good grounding in higher statistical methods, machine learning and Python. I joined thinking I wanted to do one type of PhD but ended up doing a completely different one due to the flexibility that was provided in finding/forming a PhD during the masters year. The ITT structure with industry gave relevance to our research and allowed application to differing areas which we may not otherwise be exposed to. Having a cohort structure of similar themes simultaneously provided colleagues in similar areas who I could discuss my work with but sufficient breadth that I was exposed to different mathematical areas which gave me a better background as a mathematician. The structure of the CDT provided a good sense of inclusion between the students and academics, and a wider feel of community compared to a typical PhD/Supervisor dynamic.
I am currently the statistician within the Women’s Health Research Unit at Queen Mary University London, where I am working on a wide array of studies including clinical trials, meta-analysis and large data studies, using methods that I learned during the PhD. I am grateful to SAMBa for the exposure to differing research areas and examples of the link between university research and the wider community/industry.
SAMBa’s most remarkable feature is the variety of study options it offers
Shortly after joining SAMBa I broke my neck in a bicycle accident. But thanks to the support from the amazing team, I was still able to make a success of my PhD. The SAMBa environment surrounds you with wonderful people and fantastic opportunities.
The SAMBa team understands how to efficiently bridge the gap between the abstract world of mathematics and statistics to industrial research
SAMBa provided a uniquely supportive yet challenging environment, in which one is encouraged to explore their interests and question their limits
The ITTs were invaluable in providing experience in collaborating effectively with others on large projects, understanding and synthesising new information quickly, and liasing with academic leads and commercial partners
Being a part of SAMBa was a great way to broaden my research interests and to apply this knowledge to cross-displinary problems
(My supervisors) encouraged me to take my own research direction, guided by my interests, and to be involved in the wider community, presenting at and attending a wide range of national and international conferences
Being part of SAMBa is like being part of a little community: everyone is super supportive and there is always someone to talk to if you need it (usually with cake!).
I was able to use the SAMBa training in statistics, to support training workshops in Mexico and in fact took a break from my PhD to take on a statistics teaching assistant role.
SAMBa offers high level training in statistical and applied mathematical disciplines, as well as direct engagement with industrial partners