Statistical methodology and development of new probabilistic techniques inspired by applications.
Statistical methodology and development of new probabilistic techniques inspired by applications, including research in stochastic and probabilistic modelling and inference in stochastic systems.
This is an area of strength for the UK and importance for many scientific disciplines. Despite substantial growth since 2015, demand is undiminished for qualified statisticians with an understanding of application areas including data analytics, healthcare modelling and artificial intelligence.
Statistics and applied probability research has major impacts in many areas, as evidenced by its contribution to EPSRC’s organisational priorities. It is a major contributor to advances in data science, healthcare and the digital economy.
We will develop a focus on statistics, in order to balance the research area, and we will encourage applications with a high proportion of fundamental statistics. This can be coupled with applied probability, fundamentals for AI, big data or model development, but the majority of the work must fall under the remit of statistics.
This strategy aims to build on recent investment in the area (such as the Alan Turing Institute), address capacity issues throughout the ‘people pipeline’ and respond to growing demand across all sectors of economy and society by growing investment and supporting people at all career stages within this research area.
Developing our portfolio
We will support research and training that builds on and complements previous and current work, including activities by the Alan Turing Institute.
This will mean maintaining support for core fundamental statistical methodologies, while developing links with more applied areas of statistics across the entire research landscape, both within EPSRC’s domains and more broadly.
Outputs from the Statistics and Applied Probability Landscape Event (STAPLE) will be used to develop a highly collaborative portfolio.
Supporting the GCRF
We will support research aligned to the Global Challenges Research Fund (GCRF), for example in the areas of uncertainty and epidemiology.
We will respond to the growing demand for people with skills in statistics and applied probability, particularly at the early-career stage. It is important to ensure that people have skills across all areas of statistics and applied probability, as well as spanning key topics such as machine learning, data analytics, uncertainty quantification and medical statistics.