Job reference: SAE-021444
Salary: £41,728 to £55,803 per annum dependent on family circumstances (in line with Marie Curie Pay scales)
Faculty/Organisational Unit: Science and Engineering
Location: Oxford Road
Employment type: Fixed Term
Division/Team: Department of Materials
Hours Per Week: Full time
Closing date: 03/04/2023
Contract Duration: Fixed term for three years
School/Directorate: School of Natural Sciences

Job Description

University of Manchester seeks a dedicated candidate for a 3- years PhD position in the

interdisciplinary field of X-ray imaging and advanced composite materials. As PhD student, you will be part of the Henry Moseley X-ray Imaging Facility and the Northwest Composites Centre in the Department of Materials where we develop real time imaging techniques for advanced composite materials in relation to manufacturing and recycling processes. 

This PhD project will be part of the Marie Skłodowska-Curie Action Doctoral Network (MSCA DN) “Real-time characterization of anisotropic carbon-based technological fibres, films and composites” (RELIANCE). The network is concerned with R&D and training in X-ray imaging and scattering tools and its applications in materials and information science. The network offers in total 14 PhD positions. The RELIANCE network brings together many PhD students to work on developing and implementing depth-resolved multimodal X-ray imaging and scattering tools that will enable the automated real-time characterization at the nanoscale of the structure and morphology of materials, devices, and their manufacturing processes, reliably and with precision. The methodologies developed by RELIANCE will be implemented for optimizing and controlling the processing of high-performance polymeric materials and composites, i.e., solution-spinning of aramid fibres, compaction heat stretching of polyethylene film, and pultrusion of composites. RELIANCE will significantly improve quality control of a wide range of technological materials used in composite materials. Through integration of real-time data analysis and process parameters by application of machine learning, the methods will lend themselves to Industry 4.0 solutions relying on cyber physical systems for decentralized decisions based on actual, current structural properties observed during processing.

This PhD project will focus on developing tools and techniques for real time analysis of waviness, kinking and other tow defects in composites, both virgin and recycled. Machine learning tools may be employed to identify and enhance image quality. The prototyping system will be developed in the lab to simulate continuous composites manufacturing processes. 

Via the mandatory network training provided by RELIANCE, the candidate will participate in summer schools, workshops, and scientific meetings together with top scientists and 13 fellow PhD students in the RELIANCE network. The candidate will also carry out a secondment to an industry partner and/or network partner.

Students recruited to the UKRI Doctoral Networks must not have spent more than 1 year (365 days) out of the last 3 years in the UK at the point when they are recruited to the Network

If you are unable to go online you can request a hard copy of the details from The Directorate of Human Resources, Faculty of Science and Engineering, Tel: +44 (0) 161 275 8837, Email: ​​​​​​​

The Department of Materials is strongly committed to promoting equality and diversity, including the Athena SWAN Charter for gender equality in higher education. 

We particularly welcome applications from women for this post. As an equal opportunities employer we welcome applicants from all sections of the community regardless of age, sex, gender (or gender identity), ethnicity, disability, sexual orientation and transgender status.  Appointment will always be made on merit.  For further information, please visit

The University will actively foster a culture of inclusion and diversity and will seek to achieve true equality of opportunity for all members of its community.

Enquiries about the vacancy, shortlisting and interviews:

Name: Philip Withers or Prasad Potluri

Email:   or ​​​​​​​

General enquiries:


Technical support:​​​​​​​

This vacancy will close for applications at midnight on the closing date.

Please see the link below for the Further Particulars document which contains the person specification criteria.​​​​​​​

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