Closing date: Monday, November 30, 2026
Funding: Funded PhD Project (UK Students Only)
Supervisors: Prof Keith Worden, Dr Aidan Hughes, Dr George Tsialiamanis
About the Project
Are you keen to apply advanced data science and machine learning to tackle major real-world engineering challenges? Manufacturing complex, high-performance components in aerospace and automotive engineering is a highly demanding task. Currently, getting a new process right requires finding a custom combination of speeds, feeds, toolpaths, and parameters via extensive trial and error, consuming substantial time, materials, and engineering resources.
This PhD project strives to establish Population-Based Manufacturing (PBM), a novel framework that intelligently transfers knowledge and data from existing manufacturing processes to new ones. Inspired by population-based structural health monitoring, PBM combines grammar-based modelling (representing manufacturing sequences as structured, rule-governed “languages”) and machine learning transfer learning. By extracting and adapting knowledge in a principled, mathematically-thorough way, the system provides a confident, data-informed “warm start” to process optimisation rather than the costly “cold start” industry currently relies upon.
Objectives
As the PhD researcher on this project, your core objectives will be to:
- Develop a grammar-based modelling framework capable of representing a range of manufacturing processes, including machining and assembly sequences, as structured, comparable entities.
- Build a population of process models and establish transfer-learning algorithms to move knowledge between them with reliable quantification of uncertainty.
- Demonstrate the framework on real manufacturing problems, encompassing both the optimisation of new processes and the health monitoring of existing ones to enable earlier detection of tool wear, process drift, and quality degradation.
- Lay the foundations for a connected, intelligent manufacturing ecosystem in which process knowledge is cumulative and reusable across components, machines, and facilities.
Training and impact
This research will deliver significant impact by helping manufacturers reduce the time and cost of introducing processes, shorten qualification periods, and improve product quality in high-value sectors. You will contribute directly to national ambitions around industrial digitalisation while pioneering an entirely new research direction in population-based engineering methodologies.
Working at the frontier of digital manufacturing, you will develop broad and highly transferable skills across machine learning, data science, and engineering. If you are a motivated student seeking to conduct groundbreaking research with tangible benefits to industry, we want to hear from you!
Benefits
- Earn While You Learn: Get a fully funded four-year postgraduate research degree (EngD or PhD) with an annual tax-free stipend of £28,000 (that’s equivalent to a £34,000 salary!). We’ve got your back so you can focus on your research.
- Serious Funding: You’ll have access to a £35,000 research training support grant over four years. Whether it’s for experimental work, conference travel, or the latest computing gear, we’ll make sure you have the resources to succeed.
- Work with the Best: Team up with industry giants to work on real-world projects that make a difference, gaining experience that sets you apart.
- Launch Your Career: Our graduates have landed senior roles in top industries, thanks to the hands-on experience and industry connections you’ll build here.
- World-Class Facilities: You’ll be working at the cutting edge, alongside experts in machining, assembly, and digital engineering. The tools and knowledge you’ll gain are second to none.
- Tailored Training: Benefit from both group-based and personalised training activities. We’ll help you craft an individual training plan that aligns with your career goals.
- Live in Sheffield: Enjoy life in one of the UK’s friendliest cities. With a vibrant social scene and supportive community, Sheffield is the perfect place to live and learn.
- Go Pro: We’ll support you in gaining Chartered Engineer (CEng) status, ensuring you’re recognised for your professional expertise.
Requirements
A first-class or strong 2:1 degree in a relevant science or engineering subject such as Mechanical Engineering, Aerospace Engineering, Materials Science, Physics or Computer Science
If you haven’t previously been educated in English, you’ll need an overall IELTS score of 6.5 with at least 6.0 in each section
Eligibility
This project is open to Home (UK) students. To be considered a UK Home student, you must have no restrictions on how long you can stay in the UK, and should have been ordinarily resident in the UK for at least 3 years prior to the start of the scholarship.
Interested?
Contact [contact details available in the full listing] for more information or apply here: www.sheffield.ac.uk/made4manufacturing/how-apply
When applying, please make sure you select ‘Doctoral Training Course’ as the qualification you are applying for. You should then select ‘MADE4 Manufacturing CDT’ for the specific doctoral training course, choosing either EngD or PhD as indicated in the project title.
How to apply
Ensure you have familiarised yourself with our website before making your application. The How to Apply and FAQs pages are of particular importance.
Applications are made only via the University of Sheffield admissions system. With your application, you will need to upload copies of the following:
- Complete transcripts (and final degree certificates where available). If your qualification documents are in a language other than English, you will need to supply translated versions in addition to the originals.
- Your Curriculum Vitae (CV)
- A personal statement
- If you haven’t previously been educated in English, you must provide evidence of your English language ability
Learn More
MADE4Manufacturing CDT: www.sheffield.ac.uk/made4manufacturing
Funding Notes
We provide fully-funded four-year scholarships to our CDT students that cover tuition fees, plus an annual tax-free stipend of £28,000 (equivalent to a £34,000 taxable salary). Each student also has access to £35,000 each across the four years, which can be used for equipment, conference attendance, travel and project consumables.
