PhD Studentship: Predicting and Improving the Quality of Recycled Plastics Using Advanced Metrology and Data Science

Department: Materials
Title: Predicting and Improving the Quality of Recycled Plastics Using Advanced Metrology and Data Science
Application deadline: 29/04/2025
Research theme: "Materials Characterisation" "Data Science and Machine Learning in Materials" "Plastics Recycling and Circular Economy"
How to apply: https://uom.link/pgr-apply-2425

How many positions: 1

This 3.5 year PhD is open to UK nationals. The successful candidate will received a tax free stipend set at the UKRI rate (£19,237 for 2024/25) and tuition fees will be paid. 

The transition to a circular economy requires innovative solutions to improve the quality and consistency of recycled plastics, which are vital for reducing waste and environmental impact. Recycled plastics often suffer from high variability, making it challenging for industry to predict and optimise their performance for specific applications. This PhD project seeks to address these challenges by combining advanced metrology, data science, and machine learning to develop predictive models and new standards for recycled plastics.

Based at the University of Manchester, in collaboration with the National Physical Laboratory (NPL) and Waters-TA Instruments, this project will investigate key measurement techniques, such as thermal analysis, rheology, and mechanical testing, to characterise the properties of post-consumer recyclates. The project will apply cutting-edge data science techniques, including principal component analysis and machine learning, to handle multivariate datasets and enhance predictive accuracy.

As part of the project, the successful candidate will receive training in advanced experimental techniques and data analysis, collaborate with world-leading experts in materials science and metrology, and contribute to sustainable solutions for the plastics industry. This includes access to professional development opportunities, industry skills training and cohort events offered through the Postgraduate Institute for Measurement Science [npl.co.uk] (PGI) at NPL. The project will also include placements at NPL and Waters-TA Instruments, with opportunities to work in their state-of-the-art facilities. 

Key Features of the Studentship:

Collaboration with leading organisations in recycling, metrology, and instrument development.

Training in advanced metrology, data science, and machine learning.

Opportunities to work with industry partners and national facilities.

Research aligned with the development of standards for the recycled plastics sector. 

Applicants should have, or expect to achieve, at least a 2.1 honours degree or a master’s (or international equivalent) in a relevant science or engineering related discipline 

To apply, please contact the main supervisor, Dr Thomas McDonald - thomas.mcdonald@manchester.ac.uk. Please include details of your current level of study, academic background and any relevant experience and include a paragraph about your motivation to study this PhD project.

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