Data-Centric Engineering is the emerging field at the interface of data science and all engineering fields.
It uses mathematical (often physics-based) models enhanced with experimental or statistical data sets. Data sets can be very large in some cases leading to the use of big-data methodologies. These approaches are increasingly wide-spread across mechanical, aeronautical, materials, electrical, and chemical engineering disciplines.
If you are interested in one or more examples of research projects offered by supervisors as part of our CDT in Data-Centric Engineering, please contact the supervisor(s) listed to discuss your research interests before you submit your application (EDS only).
If you have your own research idea instead, or if you are a PDS applicant, please explore the links to each of our 5 Schools below and read the guidance on how to find and contact a prospective supervisor.
- School of Electronic Engineering and Computer Science
- School of Engineering and Materials Science
- School of Physical and Chemical Sciences
- School of Biological and Behavioural Sciences
- School of Mathematical Sciences
Our major research themes in Data-Centric Engineering include:
Research in Digital Creative Industries
Materials Science and Condensed Matter Physics
Control and Systems Engineering