Skip to main content
Data-Centric Engineering

Training Programme

The CDT in Data-Centric Engineering offers a novel, enriched and integrated experience in applied research by adopting a high-level, student-centred, cohort approach to research and professional training.

Through the programme we hope to build a world-class cohort of high-tech entrepreneurs and technology leaders who have followed non-typical routes to doctoral training. 

Our Doctoral Scholars will enrol on a 4 year full-time (or 7 year part-time) programme and qualify with an Engineering Doctorate (EngD) in Data-Centric Engineering.

As a Doctoral Scholar you will have the opportunity to apply research in industry settings and receive supervision from an experienced academic from Queen Mary.

Additional training benefits include:

  • bespoke support from an assigned academic mentor
  • access to all research facilties including high performance computing as appropriate
  • funding to attend international research conferences
  • financial assistance for child-care or carers during residential activities away from home 

What you'll learn 

The training comprises a four-year programme, with an integrated programme of taught courses, workplace based research projects and professional development training (from the Queen Mary Doctoral College and industry partner offerings) running throughout. 

 The programme has four main pillars:

  1. Advanced taught courses: a bespoke programme of 6 taught courses in years 1-3
  2. Researcher development training of the cohort throughout years 1-4
  3. Industry placement throughout years 1-4
  4. Research projects throughout years 1-4

In years 1-2, students attend 3 core research courses that specifically train students in research ethics / methods / integrity, project management, statistics and engineering mathematics, and machine learning. The 3 core courses are:

  • Statistical Thinking and Engineering Mathematics
  • Research Methods and Responsible Innovation
  • Machine Learning

Electives include over 30 relevant data intensive science and engineering courses available at Queen Mary across the Faculty of Science and Engineering (subject to the approval of the supervisor and Director of Training). A list of course options will be made available to students in advance of making their course choices.