At a Glance
- Tasks: Develop innovative models for large-scale additive manufacturing and enhance quality regulation.
- Company: University of Manchester, a leader in research and innovation.
- Benefits: Fully funded PhD with a tax-free stipend and paid tuition fees.
- Other info: Applications accepted year-round; excellent opportunity for career advancement in research.
- Why this job: Join a cutting-edge project that tackles real-world challenges in sustainable production.
- Qualifications: UK 2.1 honours degree in relevant engineering or computer science fields.
The predicted salary is between 21805 - 21805 £ per year.
Application deadline: All year round
Research theme: Additive Manufacturing, Process Control
This 3.5-year PhD project is fully funded; students who are eligible to pay tuition fees at the Home rate are eligible to apply. The successful candidate will receive an annual tax‑free stipend set at the UKRI rate (£21,805 for 2026/27) and tuition fees will be paid. We expect the stipend to increase each year. The start date is October 2026. The project is expected to start in September 2026, but applications will be accepted throughout the 2026/27 academic year, subject to availability.
Large‑scale additive manufacturing (AM) is a key enabler of sustainable, decentralised production for aerospace, renewable energy and infrastructure components. Autonomous and mobile AM platforms further extend this capability by replacing oversized gantries with coordinated motion. However, scaling AM to large volumes introduces severe challenges in process stability and quality regulation: geometric errors accumulate layer by layer due to thermal effects and deformation, while intra‑layer deposition dynamics remain highly nonlinear and sensitive to force, material and environmental variability. Conventional feedback controllers and offline‑calibrated parameters become ineffective under such varying operating conditions.
This PhD will develop a multiscale, control‑oriented learning framework that delivers stable, robust and physically interpretable quality regulation for large‑scale AM. Two challenges will be addressed:
- How to establish a control‑oriented data‑driven model for nonlinear deposition dynamics;
- How to develop multiscale predictive quality regulation under uncertainty.
The developed techniques will be validated through simulation and experimental studies on representative large‑scale AM platforms available at UoM.
Applicants should have or expect to achieve at least a UK 2.1 honours degree in Mechanical and Mechatronic Engineering, Manufacturing Engineering, Computer Science or related disciplines. Experience in CAD/CAM, autonomous system and robotics development will be an advantage.
To apply, please contact the main supervisor; Dr Kun Qian - kun.qian@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.
PhD Studentship: Control-Oriented Modelling and Predictive Quality Regulation for Large-Scale A[...] in Manchester employer: The University of Manchester
The University of Manchester offers an exceptional environment for PhD candidates, particularly in the field of Additive Manufacturing and Process Control. With a fully funded studentship that includes a competitive tax-free stipend and paid tuition fees, students are supported in their academic journey while engaging in cutting-edge research. The collaborative work culture fosters innovation and personal growth, making it an ideal place for aspiring researchers to thrive.
Contact Details:
The University of Manchester Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land PhD Studentship: Control-Oriented Modelling and Predictive Quality Regulation for Large-Scale A[...] in Manchester
✨Tip Number 1
Network like a pro! Reach out to current PhD students or faculty members in your field. They can provide insider info about the application process and might even put in a good word for you!
✨Tip Number 2
Tailor your approach! When contacting Dr Kun Qian, make sure to highlight your relevant experience and how it aligns with the project. A personalised message shows genuine interest and can set you apart from the crowd.
✨Tip Number 3
Show off your passion! In your motivation paragraph, don’t just list your qualifications—share why this PhD project excites you. Let your enthusiasm shine through; it can make a huge difference!
✨Tip Number 4
Apply through our website! It’s the easiest way to ensure your application gets seen. Plus, we’re always on the lookout for candidates who fit our vision, so don’t hesitate to hit that apply button!
We think you need these skills to ace PhD Studentship: Control-Oriented Modelling and Predictive Quality Regulation for Large-Scale A[...] in Manchester
Some tips for your application 🫡
Get to Know the Project:Before you start writing, take some time to really understand the PhD project. Dive into the details about additive manufacturing and the specific challenges mentioned. This will help you tailor your application and show us that you're genuinely interested.
Show Off Your Skills:Make sure to highlight your academic background and any relevant experience, especially in Mechanical and Mechatronic Engineering or related fields. If you've got skills in CAD/CAM or robotics, don’t hold back! We want to see how you can contribute to the project.
Craft a Compelling Motivation Paragraph:When you write about your motivation for this PhD, be specific! Tell us why this project excites you and how it aligns with your career goals. A personal touch can make your application stand out from the crowd.
Apply Through Our Website:Don’t forget to submit your application through our official website. It’s the easiest way for us to keep track of your application and ensures you’re following the right process. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at The University of Manchester
✨Know Your Stuff
Make sure you have a solid understanding of additive manufacturing and process control. Brush up on the latest trends and challenges in the field, especially those related to large-scale applications. This will show your passion and commitment to the subject.
✨Showcase Relevant Experience
If you've got experience in CAD/CAM, autonomous systems, or robotics, be ready to discuss it in detail. Prepare specific examples of projects you've worked on that relate to the PhD topic. This will help demonstrate your practical skills and how they align with the research.
✨Ask Insightful Questions
Prepare thoughtful questions for Dr Kun Qian about the project and its challenges. This not only shows your interest but also helps you gauge if the project aligns with your career goals. Think about aspects like the expected outcomes and potential collaborations.
✨Express Your Motivation
Craft a compelling narrative about why you want to pursue this PhD. Highlight your passion for sustainable production and how you see yourself contributing to the field. A strong motivation statement can set you apart from other candidates.
