The Midlands Centre for Data-Driven Metrology

Centre for Doctoral Training

The MCDDM Centre for Doctoral Training will provide a pipeline of trained engineers with expertise in digital manufacturing and metrology techniques. Starting in October 2021, a number of positions will be available to those interested in undertaking advanced study and research in these fields.

Doctoral positions are supported by industrial partners of the MCDDM, and supervised by academics of the University of Nottingham, Lougborough University, and Coventry University. Competitive funding for positions will be available to high-quality UK candidates. Standard admission requirements of each University, including academic and language requirements, will apply to these positions. 

Please find below a list of suggested topics for doctoral study, along with details of the supervising academic(s). If you are interested in applying for these projects, please contact Katie Blake as an expression of interest in the first instance.

Send an expression of interest

Cohort Activities

In addition to research projects, doctoral students will gain access to academic skills training and industry mentorship. Students will also take part in team building activities, and attend world-class conferences and research events. Cohorts will also take part in outreach activities and will organise an annual CDT conference to present ongoing research topics. 

Current Topics

Topics listed are areas of study offered by the research groups of the Midlands Centre for Data-Driven Metrology. Within the details of each project title you will find information on the supervising academics and the primary location of study for that project.

Creating digital twins using AI for automation and robotics

Primary location of study: Loughborough University 

Supervisory team: Dr Niels Lohse, Dr Peter Kinnell

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Fibre optic sensing for in-process manufacturing measurements in harsh environments

Primary location of study: Loughborough University

Supervisory team: Dr Laura Justham, Dr Jon Petzing, Dr Peter Kinnell

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In-process sensing and machine learning for surface measurement

Primary location of study: University of Nottingham

Supervisory team: Dr Nicholas Watson, Professor Richard Leach

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Intelligent 3D scanning for complex objects

Primary location of study: University of Nottingham

Supervisory team: Dr Samanta Piano

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Investigation into the sources of uncertainty in the optical measurement of gears

Primary location of study: University of Nottingham

Supervisory team: Professor Richard Leach

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Metrology in the context of future 5G-enabled manufacturing systems

Primary location of study: Loughborough University

Supervisory team: Dr Peter Kinnell, Dr Jon Petzing

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Quantifying the measurement capabilities of point cloud data across different measurement systems

Primary location of study: Coventry University

Supervisory team: Dr Ranveer Matharu, Professor Trevor Toman

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Quantum surface metrology

Primary location of study: University of Nottingham

Supervisory team: Dr Samanta Piano

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Real-time control of robots in highly uncertain environments

Primary location of study: University of Nottingham

Supervisory team: Dr David Branson

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Sensors for enhanced control in robotic 3D printing

Primary location of study: Loughborough University

Supervisory team: Professor Richard Busswell, Dr Peter Kinnell

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Uncertainty evaluation with point cloud data

Primary location of study: University of Nottingham

Supervisory team: Professor Richard Leach

Project detail download