Other PhD Scholarships Available in Design Engineering

Supervisor: Dr Mazdak Ghajari

Location: Dyson School of Design Engineering, Imperial College London

Funding: This call is for strong candidates to contact Dr Ghajari to discuss possible scholarship opportunities. More details are provided below.

Overview

Mechanical loading plays a key role in a range of neurological conditions. An example is traumatic brain injury (TBI), which is caused by brain exposure to mechanical loading in sports and road traffic collisions. Mechanical loading can damage brain tissue, axons and vasculature, leading to short and long-term deficits. Understanding the relationship between loading and brain injury is key to predicting brain injuries and preventing and managing their consequences.

The HEAD lab at Design Engineering, Imperial College London, is offering exciting PhD opportunities in the field of biomechanics of brain injury. These involve combining computational modelling, experimental work and neurological studies, and translational applications for real-world impact. Our vision at HEAD lab is to improve brain health through developing technologies that help predict, prevent and manage brain injuries.

Project areas

We are seeking highly motivated PhD candidates to work with us. Below you can find some areas of our current work, but please note that this is not an exhaustive list, and we consider research proposals that are aligned with our vision.

1. High-fidelity individualised brain injury prediction models

• Develop multi-scale brain injury prediction models for individuals
• Validate predictions using large-scale instrumented mouthguard data and brain injury biomarkers

Applications: i) contributing to our understanding of the links between mechanics and brain injury, ii) predicting brain injuries in a range of contexts, e.g. sports and road safety, and iii) guiding the design of better prevention strategies and test methods

2. Brain injury thresholds

• Determine thresholds for producing different types of brain injuries.
• Develop accessible metrics and corresponding thresholds for predicting brain injuries in different applications.

Applications: i) brain injury risk management, ii) prevention strategies assessment and design,

3. Near-real-time brain injury prediction models

• Develop surrogate models for brain injury prediction using novel techniques such as physics-informed/embedded machine learning
• Incorporate explainability for medical applications

Applications: i) pitch-side brain injury assessment, ii) brain injury monitoring after road traffic collisions for rapid response

4. Subject-specific biomechanical modelling of normal pressure hydrocephalus

• Develop individualised biomechanical models of ventricular expansion
• Validate models against imaging biomarkers
• Develop computational pipelines for rapid prediction of brain tissue responses to ventricular expansion.

Applications: i) apply biomechanical insights to understand progression of hydrocephalus, and ii) inform diagnosis and early interventions.

5. Brain injury metrics and thresholds for children

• Develop new computational models of brain injury prediction in children
• Determine metrics for predicting injuries in children in contexts, such as cycling
• Determine injury thresholds using multi-modal data

Applications: i) an extension of the HIPER (www.hiperhelmets.org) rating to children’s cycle helmets, ii) inform new standards, such as the children’s cycle standards, iii) surveillance system for community and school sports.

6. Representative helmet test methods

• Determine prevalent causes of brain injuries in different applications
• Identify representative impact conditions using a combination of advanced computational modelling, experimental testing and data
• Assess a range of prevention strategies to validate the conditions

Applications: i) inform the design of helmets, ii) guide future helmet standards, and helmet ratings.

Why join us?

Candidates will have the opportunity to

1. Work within an internationally recognised team
2. Collaborate with experts in brain sciences, computational modelling and artificial intelligence
3. Access unique large-scale exposure data, objective measurements of brain injury and clinical assessments in human
4. Embed human centred approaches in the design and delivery of their studies
5. Incorporate translational thinking from the outset
6. Access immediate pathways for delivering impact, such as our highly successful cycle rating system, Hiper: hiperhelmets.org
7. Access a large network of stakeholders, from industry, policymakers, standards, governing bodies and end-users
8. Take part in teaching and lab demonstration as paid graduate teaching assistants

Candidate Profile

• A high 2:1 (Merit) degree or equivalent at Master’s level in engineering, physical sciences, or a related discipline.
• Strong quantitative, programming, or modelling skills.
• Highly motivated to be part of an interdisciplinary team and work with engineers and clinicians.
• Strong interest in translational applications of biomechanics in medicine, healthcare, sports and road safety.
• Good communication skills

Funding

• Scholarships: Strong candidates may be considered for a range of scholarships such as the Imperial President’s PhD Scholarship, IC-CSC, Lee Family, CDTs, etc. The list of scholarships can be found here: https://www.imperial.ac.uk/design-engineering/study/phd/funding-opportunities/.
• Industry funding: strong candidates may be considered for opportunities that require some industry funding and nominating a strong candidate.
• Self-funded students: Applicants with independent financial support can also apply, but they should have a very strong academic profile.

How to Apply

To express interest, please send the following to m.ghajari@imperial.ac.uk:

• CV
• Academic transcripts
• A motivation letter (max 1 page)

Hundreds of billions of tons of copper (Cu) sit idle in difficult to process mine waste sites. Novel solutions are needed to liberate this unrecovered Cu to meet the demand for manufacturing electronics and clean energy technologies, and so that mine sites can be remediated to protect the environment. The proposed research aims to address the critical challenge of recovering copper (Cu) from low-grade mine waste, a significant untapped resource estimated to contain hundreds of billions of tons of Cu. This study seeks to develop innovative biointegrated material architectures for Cu hyperaccumulation, combining expertise from design engineering, microbiology, bioprocessing, and waste management. The primary objective is to create an optimized organism suite integrated into inert scaffolds for controlled Cu accumulation from waste brines and tailings. This approach aims to enhance the efficiency and selectivity of Cu recovery compared to traditional methods. To achieve this, we will investigate and select microorganisms with high Cu accumulation capacity, focusing on their ability to thrive in the harsh conditions typical of mine waste environments. Inert scaffolds will be engineered to optimize surface area for microbial colonization, mass transfer of Cu ions, and structural integrity under process conditions. Key factors to be studied include nutrient availability for microbial growth, microclimate control within the scaffold, tortuosity effects on Cu ion transport, mechanical stability of the bio-integrated system, and chemical fixation mechanisms for Cu retention. The research will focus on developing a large-volume biochemical copper isolation process that emphasizes interface optimization between organisms and scaffolds, geometric configurations for enhanced Cu selectivity, and scalability of the bio-integrated system. This project synthesizes knowledge from multiple disciplines: design engineering for scaffold architecture and process integration; microbiology for organism selection and optimization; bioprocessing for scaling up and process efficiency; and circular economy for sustainable resource recovery models. The expected outcomes include novel bio-integrated material architectures for Cu

hyperaccumulation, improved understanding of organism-scaffold interactions in metal recovery, a scalable and environmentally friendly Cu recovery process, contributions to mine site remediation strategies, and advancements in circular economy approaches for metal recovery. Hosted by the Dyson School of Design Engineering, this research aims to provide a sustainable solution to the grand challenge of copper recovery from waste, potentially revolutionizing resource extraction in the mining industry while addressing environmental concerns.

Funding Notes

This highly prestigious PhD Scholarship will enable funding for three years of research of a UK home students or an international student. The research will also include secondments at ANU and UBC and participation in annual Rio Tinto Research Conferences. We are looking for students from Bioengineering, Design Engineering, Biochemistry or Chemical engineering, or another related disciplines with Passion for sustainable design and research who are interested working on an international transdisciplinary research project with the potential for impact at scale. The candidate will have the opportunity to interact with a transdisciplinary network of researchers and other PhD students from the fields of microbiology, environmental sciences, chemical engineering and earth science engineering.

The Rio Tinto Centre for Future Materials is a $150M, 10-year, multidisciplinary, global effort to deliver a step-change in the approach to materials extraction, use and reuse, in a way that is more environmentally, economically and socially sustainable in support of the Energy Transition. The Centre is hosted by Imperial College London and brings together Imperial, four global university partners (The University of British Columbia, Vancouver, The University of California, Berkeley, The University of the Witwatersrand, Johannesburg, The Australian National University, Canberra) and Rio Tinto.

For application enquiries, please contact Dr Elena Dieckmann: Elena.dieckmann13@imperial.ac.uk

Applications must be submitted by 30/04/2025. 

About the project: Applications are invited for an exciting PhD research project in the interdisciplinary field of artificial intelligence (AI) powered manufacturing and structural design for lightweight vehicles leading to the award of a PhD degree. This studentship is funded by an EPSRC iCASE award and industrial partner Tata Steel UK.

The vision of the project is to pioneer fundamental AI methodologies to empower the creation of steel-based high-performance, manufacturable parts by holistically optimising vehicle part geometries, process settings, as well as material conditions. The aim is to lead the development of the world’s first AI-driven platform that empowers the creation of high-performance, manufacturable vehicle parts, tailored to Tata Steel UK’s products. You will join us for achieving this aim through the development of fundamental applied AI methodologies. This novel interdisciplinary project could increase effectiveness of today’s components forming simulations. The AI methodology will provide a more advanced approach for constructing AI based forming feasible deep-drawn components as well as optimising the forming strains in crash sensitive parts of a vehicle to achieve weight reduction, which could help designers choose the right geometries for blanks and tooling, the right material and gauge for vehicle components, and therefore help reduce weight, cost, and CO2, addressing real-world sustainability needs.

The project will be supervised by Dr Nan Li at Imperial College London and an industrial expert, Mr. Andrew Ruthven, at Tata Steel UK. During the project, the PhD student will have the opportunity to visit Tata Steel UK’s premises, and to disseminate the work at international conferences and industrial events.

Academic criteria: applicants must be in receipt of, or are due to receive, a first class or equivalent in an undergraduate or integrated Masters degree, in Engineering, Physics, Computing or any other relevant STEM subjects; or if a first class or equivalent has not been achieved, applicants must be in receipt of (or where this has yet to be received, be able to provide evidence of high performance that will lead to) a distinction in a standalone Master’s qualification. (A 2:1 degree is acceptable if the applicant can demonstrate significant industrial or research experience and output.)

We also expect applicants to have a demonstrable interest in innovation and interdisciplinary and translational research. In addition, good communication, team-working, and management skills are also important.

Interested applicants should send an up-to-date curriculum vitae to Dr Nan Li (nan.li@imperial.ac.uk). Suitable candidates will be required to complete an electronic application form, following the standard Imperial College application procedure; more information can be found here. For queries regarding the application process, please contact n.moult@imperial.ac.uk.

Funding Notes

This studentship covers full tuition fees at the Home rate and includes a generous stipend set at the UKRI rate plus industrial top-ups for 4 years.

According to EPSRC rules, this post will prioritise Home students. The timeframe is tight, so please contact Dr Nan Li ASAP if you are interested. The advert will be closed once the post is filled, so please apply as soon as possible if you are interested. 

3.5 year LISS DTP PhD Studentship (Home Fees) at Imperial College London

What makes people stick to a mobile game for days, months, or years? This interdisciplinary, data-intensive PhD project unpacks casual game engagement across time scales. The PhD works closely with industry partner King (now part of Microsoft Gaming), providing data access to over 200 million active players of Candy Crush Saga. The project combines longitudinal mixed methods with interpretable machine learning. Housed in the Dyson School of Design Engineering at Imperial College London, in collaboration with N/Lab at University of Nottingham, it is supervised by experts in game engagement, explainable AI, behavioural analytics, and user experience. It offers a unique opportunity to impact responsible industry practice and policy guidance in games; experience state of the art data science in the games industry; and learn advanced machine learning methods for social science.

Key info

• 3.5 years fully funded PhD (home tuition fees + £21,237 stipend per year) through an ESRC London Interdisciplinary Social Science DTP Case Studentship
• Enrolled at Dyson School of Design Engineering, Imperial College London, affiliated with N/Lab, University of Nottingham
• Close collaboration with King, makers of Candy Crush
• Supervised by Sebastian Deterding, Matthew Wicker, James Goulding, and Muriel Garreta-Domingo
• Application deadline: March 1, 2025
• Interviews: Week of March 17, 2025
• PhD start date: October 1, 2025

What you will get

• 3.5 years of full-time funding of home tuition fees (£4,786 per annum 2024/25) and a living stipend (£21,237 per annum 2024/25), plus a research budget (ca. £940 per annum) 
• Monthly mentoring by King, annual multi-day office visits at King offices, and a potential placement
• Access to and support with player recruitment and data (logs of millions of players, player surveys)
• Access to rich early career researcher and data science/AI training opportunities at the LISS DTP, Imperial Early Career Researcher Institute, and Imperial I-X
• Affiliation with the N/LAB, a global centre of excellence at the University of Nottingham in behavioural analytics and social data science, including research visits

For full details and the application process, see here. 

The partner

King is a globally leading mobile game company publishing more than 200 titles, including the highly successful Candy Crush franchise, As part of Microsoft Gaming, King has game studios in Stockholm, Malmö, London, Barcelona and Berlin and offices in San Francisco, New York, Los Angeles, Dublin and Malta. The project will work directly with the User Experience and Data Science teams at King.

Why do this PhD?

• Make a practical positive difference with models of long-term engagement that can directly inform industry practice and policy
• Learn advanced social science methods like interpretable machine learning in an applied contexts
• A committed and supportive academic and industry supervision team
• Welcoming communities of PhD students at the Dyson School of Design Engineering at Imperial College and LISS DTP across Imperial, King’s College, and Queen Mary, University of London
• Gain practical experience in state of the art industry data science in one of the most data-mature game companies world-wide
• Unique collaboration, mentoring, and networking with King let you explore and build foundations for an industry career in games research

The ideal candidate probably does not exist, but would bring …

• masters-level social science methods skills (meeting the LISS core training requirements);
• deep interest in games and ideally, familiarity with player experience and engagement literature in media psychology or HCI;
• foundations for big data science and/or machine learning, e.g., Python programming;
• familiarity with or curiosity to learn large-scale data science methods, particularly interpretable AI/machine learning approaches

Don’t worry if you don’t fit this profile perfectly! Our researchers come from all walks of life and through many twists and turns. We choose candidates on the basis of your overall potential to successfully complete this PhD and make a positive impact through research as a member of our diverse research community. We especially welcome applications from candidates belonging to groups that are currently under-represented in games research and the games industry; these include (but are not limited to) women, individuals from ethnic minorities, members of the LGBTQ+ community, people from low-income backgrounds, people with disabilities, and people with caring responsibilities.

Unsure if you should reach out and apply or not? We will run an online info session in early February you can attend. Just register your interest here: https://forms.microsoft.com/e/GBgxdP0cH9 

Application process

1. Email Sebastian Deterding (he/him, s.deterding@imperial.ac.uk) as soon as possible to leave time to discuss your fit and application. Include “LISS DTP: Casual Game Engagement” in your email subject. Plus points if you attach a current CV, an academic writing sample, and a short explanation what interests you in this position.
2. Sebastian may schedule one or more informal face-to-face or video meetings with you and him and potentially, other co-supervisors and recommend that you apply or not.
3. If you are invited, submit your full application materials by March 1, 2025 through the Imperial College Application System. Details here: https://www.imperial.ac.uk/design-engineering/study/phd/applying-for-a-phd-in-design-engineering. Sebastian will share details on how to prepare your research proposal.
4. Applications are shortlisted and shortlisted candidates invited for a formal one hour interview in the week of March 24, 2025.
5. We will let interviewed candidates know the results in the week of March 31, 2025.
6. LISS DTP will check and confirm the proposed candidate eligibility and funding and issue formal offers in the week of April 28, 2025.
7. The studentship starts October 2025.

Entrance requirements

• First Class (Distinction) Degree or equivalent at Masters level in a relevant discipline. Where extensive research/industry experience can be demonstrated, candidates with a UK-equivalent of 2:1 (Merit) at Masters level can be considered
• Meet Imperial’s English-language requirements
• Meet the LISS DTP core training requirements (masters level training in social science research methods)
• While we welcome international candidates, the studentship only pays home tuition fees, and so you need to either qualify as a home student or be able to fund the fee difference to international tuition fees from a different source. To qualify as a home student, you must meet one of the following criteria:
• Be a UK National (meeting residency requirements), or
• Have settled status, or
• Have pre-settled status (meeting residency requirements), or
• Have indefinite leave to remain or enter

Want to know more?

Contact Prof Sebastian Deterding at s.deterding@imperial.ac.uk.