WMG Warwick Manufacturing Group

Funding Source: EPSRC DLA Interdisciplinary Scholarships

Stipend:

• UKRI rate stipend for 3.5 years full-time (70 months part-time).
• Full Payment of academic fees (home only)
• A Researcher Training Support Grant of up to £5,000
• Access to Disabled Student Allowance, paid sick leave and paid parental leave

Supervisor: University of Warwick: Dr Arnab Palit, Prof Andy Metcalfe

Eligibly: Satisfy UKRI's eligibility criteria, this funding is restricted to Home fees candidates due to Council requirements

Start date: October 2025

Project Overview

Total Hip Replacement (THR) is a common surgical procedure, with nearly 100,000 performed annually in the UK. However, about 20% require revision within 15 years due to complications like implant loosening, dislocation, and fractures caused by suboptimal implant positioning. With primary THR demand in younger patients expected to increase fivefold by 2030, revision surgeries will also rise. To improve implant positioning, image-guided navigation is increasingly used in complex THR procedures. These systems combine preoperative planning and intraoperative measurements into a visual interface, improving surgical precision and outcomes. However, current navigation methods have significant limitations. They rely on artificial markers attached to bones, requiring additional incisions that increase the risk of injury and infection. The manual registration process adds 15-20 minutes to surgery, introduces human error, and creates line-of-sight occlusions, disrupting surgical workflow.

This interdisciplinary project aims to overcome these challenges by developing a vision-based marker-less navigation system using deep learning (DL). The project’s objectives include generating training data from synthetic datasets and real-world images (cadaver and actual intraoperative THR images), developing a marker-less segmentation and registration workflow, integrating with in-house THR pre-planning to create a complete navigation system, and validating it through cadaver experiments.

The proposed work will improve surgical workflow, shortens surgery time, enables unrestricted movement tracking, and reduces infection risks. Eliminating markers enables robot-assisted or fully automated femoral implantation, which is not possible with current systems. It aligns with key STEM themes and EPSRC’s strategic focus on ‘Engineering’, ‘Health and Medical Technologies’, and ‘AI, Digital, and Smart Applications’.

Warwick University is renowned for its high-quality research and a thriving PhD program. This strong research culture enhances both the PhD student’s experience and the demand for our graduates. This PhD project has been developed through interdisciplinary collaboration between Warwick Manufacturing Group (WMG), Warwick Medical School (WMS), and University Hospital Coventry and Warwickshire (UHCW) NHS Trust. It offers an opportunity to apply engineering expertise to real-world challenges, making a meaningful impact. The successful applicant will work collaboratively across WMG and WMS. While the primary focus will be on biomechanics, image processing, machine learning (ML), artificial intelligence (AI), and metrology, the student will also contribute to the co-design of cadaver experiments and data collection activities. Supervision will be provided by academics from various disciplines specializing in biomechanics, image processing, and computer vision, alongside orthopaedic surgeons and academics

Essential Criteria:

• A 1st or 2.1 undergraduate (BEng, BSc, MEng) and/or postgraduate masters’ qualification (MSc) in a relevant field, such as biomedical engineering, computer science, mechanical engineering, medical imaging, AI/ML, or a related discipline.
• Knowledge of machine learning (ML) and deep learning (DL), with hands-on experience in developing and implementing algorithms using programming languages such as Python, MATLAB, or C++ for image processing or related applications.
• A passion and enthusiasm to challenge the state-of-the-art, and ability to work independently and collaboratively in an interdisciplinary environment, engaging with engineers, surgeons, and researchers.
• Excellent written and verbal communication skills, with the ability to present research findings effectively.

Desirable Criteria:

• Experience with medical image processing (e.g., segmentation, registration) and working with synthetic or real-world datasets (CT, X-ray, intraoperative images).

• Familiarity with marker-less tracking, computer vision-based navigation, or image-guided surgery.
• Prior research experience (e.g., a published paper, research internship, or project in a relevant area).

Funding and Eligibility: 

• UKRI rate stipend for 3.5 years full-time (70 months part-time).
• Full Payment of academic fees (home only)
• A Researcher Training Support Grant of up to £5,000
• Access to Disabled Student Allowance, paid sick leave and paid parental leave.

Satisfy UKRI's eligibility criteria, this funding is restricted to Home fees candidates due to Council requirements.

Funding Source: Warwick Industrial Fellowships

Stipend: £19,237 (increasing annually)Link opens in a new window

Supporting Company: Electronic ArtsLink opens in a new window

Supervisor: University of Warwick: Prof. Kurt Debattista and Dr. Thomas Bashford-Rogers

Eligibly: Home students

Start date: July 2025

Project Overview

The University of Warwick in partnership with Electronic Arts (EA), is looking to recruit a PhD student in computer graphics for games. This is open to home students and will fully cover tuition fees and include a tax-free stipend (£19,237 pa. currently), for a period of 3.5 years. The successful candidate will be supervised by Prof. Kurt Debattista and Dr. Thomas Bashford-Rogers at the University of Warwick, and work in collaboration with the F1 Development Team at EA.

Modern game graphics is continually pushing the boundaries of visual quality and speed often with an ultimate goal of fully photorealistic game worlds. To achieve this goal, we need advances in many areas, from light transport, sampling, geometry and material representations, and computationally efficient algorithms to display technologies and understanding human perception. This studentship aims to innovate in these areas, with a particular focus on novel methods for representing and rendering game worlds in real time.

We are seeking a student with a background in Mathematics, Computer Science, or a related STEM discipline who is passionate about computer graphics and gaming. A prior interest or experience in ML/AI rendering techniques, would be an advantage. The ideal candidate will have a deep interest in the algorithms that power graphics and a creative mindset, eager to think outside the box and develop novel solutions to complex challenges in this field

Essential and Desirable Criteria: Solid foundation in computing principles, particularly computer graphics and machine learning.

A 1st or 2.1 undergraduate (BEng, BSc, MEng) and/or postgraduate masters’ qualification (MSc).

Funding and Eligibility: Home Fee StatusLink opens in a new window. Fully funded for 3.5 years, full stipendLink opens in a new window and RTSG (£5k for travel and expenses)

Key Information

Funding Source: Fraser-Nash Consulting

Stipend:£15,285

Supervisor: Professor Carsten Maple

Available to Home fee status and UK domicile EU students

Start date: June 2024

Project Overview

---

Artificial Intelligence plays a significant role in modern society and business, and this is only set to grow. The technology features in the electronic games we play, the cars we drive and the chatbots we engage with. The UK recently hosted leaders around the world for a Global AI Safety Summit, highlighting the importance of understanding and controlling how AI operates and is deployed. The UK has one of the strongest AI markets globally with continuing government support and a thriving academic and innovative technology industry. To successfully bring AI-based systems to the general public and ensure adoption and sufficient trust, there is a need for AI assurance. We are seeking applications from motivated individuals with the potential to contribute to this important scientific effort. The AI Assurance EngD will provide the successful applicant with key skills to unlocking this potential. This EngD studentship aims to train the first generation of technical leaders that will specialise in the area of AI assurance. This will be delivered through Frazer-Nash, Digital Systems Assurance group in partnership with the University of Warwick’s WMG centre. The expected duration of this program and funding is available for 4 years The EngD student will be office based in Bristol (hybrid), in a team of professional engineers and scientists and other recent graduates working on industry interesting and diverse AI and autonomy projects.

WMG, University of Warwick and Frazer-Nash Consultancy WMG is an academic department at the University of Warwick and is the leading international role model for successful collaboration between academia and the public and private sectors, driving innovation in science, technology and engineering, to develop the brightest ideas and talent that will shape our future. Frazer-Nash is a systems-engineering and technology solutions consultancy, supporting key UK and international organisations and sectors such as energy, defence, space, transport and healthcare (https://www.fnc.co.uk/). We are seeing high interest and rapid growth in the area of AI assurance and see this as a major growth area. Research Objectives The assurance of AI-based systems is a complex challenge that will require specialist skills to understand; the specific risks that AI pose, the values and principles that we should be aiming to meet, the tools and techniques needed to assess such systems and an awareness of the current standards and regulations that developers will need to meet. The research objectives are Critical analysis of current research in verification and assurance of AI systems, including tools and techniques for verification of complex systems and techniques for assessing AI systems Develop a framework for risk assessment for AI-based systems Develop and test methods for runtime monitoring of AI systems Analysis of latest AI standards and verification tools or techniques Develop an application mapping strategy that links verification techniques to AI technology and relevant standards.

Essential and Desirable Criteria

---

Good BSc or higher in Computer Science, Engineering, Cyber Security, Mathematics, Statistics or similar. Experience of working in teams and meeting deadlines.

Funding and Eligibility

Funding is available to eligible Home fee status

To apply

To apply please complete our online enquiry form and upload your CV, transcripts and certificates of previous studies to allow us to assess your suitability for this specific PhD.

Please ensure you meet the minimum requirements before filling in the online form.

Funding Source: EPSRC Industrial CASE (iCASE)

Stipend:£19,237 per annum for 4 year

Supporting Company:Tata Steel UK

Supervisor: University of Warwick: Professor Zushu Li, Dr Zhiming Yan

Available to Home fee status and UK domicile EU students

Start date: October 2024

Project Overview

---

An enthusiastic individual is being invited to join a team of researchers to work on the EPSRC (Engineering & Physical Sciences Research Council) Industrial Case funded project with industrial partner Tata Steel UK. The aim of this project is to create fundamental knowledge of biomass application in EAF (Electric Arc Furnace) steelmaking, supporting the transition to net-zero steel manufacturing.

Steel is an irreplaceable material in our modern life, while steel industry accounts for 7% of global anthropogenic CO2 emissions. A variety of low emission steel manufacturing processes, including the proven EAF route, are being developed to convert the currently dominating Blast Furnace – Basic Oxygen Furnace (BF-BOF) steelmaking route to low CO2 or CO2 free steelmaking route. In conventional EAF steelmaking, significant amount of fossil fuel such as anthracite is charged or injected into the bath to provide chemical energy and create slag foaming, which will not be possible in future scrap-based net-zero EAF steelmaking. In the scrap-based, net-zero EAF steelmaking, carbon neutral biomass could be the major carbon source to provide chemical energy and create slag foaming for the EAF process. In EAF steelmaking, foamy slag plays a critical role in covering/stabilising the arc, increasing energy efficiency, shielding the refractories from the arc plasma, and reducing the pick-up of nitrogen (N2) and other impurities, so appropriate slag foaming is extremely important to ensure the EAF increase productivity and quality at competitive costs.

Therefore, to enable CO2 free green steelmaking, this PhD project will thoroughly investigate the physical and chemical characteristics of different carbonaceous materials for the EAF Steelmaking process, with a focus on reaction mechanisms and kinetics between biomass and FeO-containing slag. The project will advance our understanding on carbon behaviour in EAF steelmaking process and provide information on physical and chemical properties required for biomass to ensure appropriate slag foaming in the net-zero EAF steelmaking.

The research will be carried out by using the world-leading research facilities (high temperature experiment, advanced characterisation and modelling) at the Advanced Steel Research Centre (ASRC) of WMG, the University of Warwick. This PhD studentship also offers a unique opportunity to work with the leading scientists at Tata Steel UK.

Essential and Desirable Criteria

---

We are actively seeking an enthusiastic individual to join the Advanced Steel Research Centre (ASRC) at WMG, the University of Warwick with the following entry requirements and expectations:

A 1st or 2.1 undergraduate (BEng, BSc, MEng) and/or postgraduate masters’ qualification (MSc) in a science and technology field such as Metallurgy, Chemistry, Chemical Engineering, Physics, Materials Science and Engineering, Manufacturing.

A passion and enthusiasm to challenge the state-of-the-art and to apply the world leading research facilities for the creation of critical knowledge and its industrial applications.

Funding and Eligibility

---

Funding of £19,237 per annum for 4 years.

Funding is available to eligible Home fee status and UK domicile EU students.

To apply please complete our online enquiry form and upload your CV, transcripts and certificates of previous studies to allow us to assess your suitability for this specific PhD.

* Please ensure you meet the minimum requirements before filling in the online form.