📋 Tender Overview
Funded Value6159464Funded PeriodApr 19 - Sep 27FunderEPSRCProject StatusActiveProject CategoryTraining GrantProject ReferenceEPS0231511The CDT will train the next generation of leaders in statistics and statistical machine learning who will be able to develop widely-applicable novel methodology and theory as well as create application-specific methods leading to breakthroughs in real-world problems in government medicine industry and science. The research will focus on the development of applicable modern statistical theory and methods as well as on the underpinnings of statistical machine learning. The research will be strongly linked to applications.There is an urgent national need for graduates from this CDT. Large volumes of complicated data are now routinely collected in all sectors of society encompassing electronic health records massive scientific datasets governmental data and data collected through the advent of the digital economy. The underpinning techniques for exploiting these data come from statistics and machine learning. Exploiting such data is crucial for future UK prosperity. However several reports from government and learned societies have identified a lack of individuals able to exploit this data.In many situations existing methodology is insufficient. Off-the-shelf approaches may be misleading due to a lack of reproducibility or sampling biases which they do not correct. Furthermore understanding the underlying mechanisms is often desired scientifically valid interpretable and reproducible results are needed to understand scientific phenomena and to justify decisions particularly those affecting individuals. Bespoke model-based statistical methods are needed that may need to be blended with statistical machine learning approaches to deal with large data. Individuals that can fulfill these more sophisticated demands are doctoral level graduates in statistics who are well versed in the foundations of machine learning. Yet the UK only graduates a small number of statistics PhDs per year and many of these graduates will not have been exposed to machine learning.The Centre will bring together Imperial and Oxford two top statistics groups as equal partners offering an exceptional training environment and the direct involvement of absolute research leaders in their fields. The supervisor pool will include outstanding researchers in statistical methodology and theory as well as in statistical machine learning.We will use innovative and student-led teaching focussing on PhD-level training. Teaching cuts across years and thus creates strong cohort cohesion not just within a year group but also between year groups. We will link theoretical advances to application areas through partner interactions as well as through a placement of students with users of statistics.The CDT has a large number of high profile partners that helped shape our application priority areas digital econom
