Data Visualisation Doctor of Philosophy - PhD

Study for a Data Visualisation PhD at Warwick's innovative and diverse Centre for Interdisciplinary Methodologies. Join an innovative, cohort-based PhD, with theoretically grounded and practice-led research structured through linked projects on diverse data visualisation research questions.

Science, industry and society need people with advanced data visualization capabilities. Studying for a PhD in visualisation at the Centre for Interdisciplinary Methodologies (CIM) at Warwick is an opportunity to undertake world-leading doctoral research and join a cohort of future leaders in data visualization.

The Data Visualisation PhD programme provides you with the academic and professional opportunities to develop as an independent, creative and impactful researcher who can contribute to knowledge and research at the forefront of data visualisation and data science research.

You will pursue a programme of study consisting of several doctoral level components. These components will ordinarily be in the form of research projects undertaken with either external organisations (commercial, not-for-profit or academic) or internal academic units. You will document and develop your research in interactive digital notebooks in line with best practice in data visualization research and submit your notebook as a digital thesis for examination.

Within this PhD, you will join the cohort of EPSRC Diversity in Data Visualization Centre for Doctoral Training, DIVERSE CDT that is co-hosted at CIM at Warwick together with City, St Georges, University of London. As well as the interdisciplinary academics at CIM, you will interact with the whole academic team of DIVERSE CDT across the two universities during your studies.

CIM is one of the very few places where the development of interdisciplinary methodology is the focus. Data Visualisation is a key research area for several academics at CIM and you will benefit from tailored guidance from academics and professional staff with experience and expertise in the challenges of interdisciplinary data visualisation research and interdisciplinary methods overall.