Doctoral scholarships

Project advert

Cutting-edge research to improve green hydrogen production

The Coriolis mass flowmeter (CMF), is among the most accurate mass flowmeter products, and is widely used in the oil & gas, water & wastewater industries across the globe. CMFs determine the mass flowrate based on the phase shift of vibration of one or more flow tubes. However, the coupling effect of flow performance and vibration of structure, as the underlying mechanism of CMF operation, is not considered in the CMF model due to the challenge to solve the multiple partial differential equations simultaneously. 

With the support of the combined sponsorship from the university and industrial partner, this project aims to develop a novel modelling and analysis approach to address the mathematical and technical challenges of the fluid-structure interaction (FSI) mechanisms globally. The successful PhD candidate will drive the development of FSI model to simulate the effect of fluid-solid coupling effect on the vibration of the structure. The successful candidate will work with the multidisciplinary academic team in the newly built Dalton Building with the state-of-the-art facilities equipped. Working with the industrial partner will hugely enhance the students’ capability to apply theoretical knowledge across the wide range of technical scope, along with support in validating the novel models experimentally.

Project aims and objectives

This project aims to develop a novel approach to analyse the interaction between the structure of CFM and dynamic performance of the flow. The aim will be achieved through the following objectives:

1. Develop a novel approach to investigate the fluid-solid coupling effect on the performance of the CMF;
2. Using machine-learning (deep learning) methods to develop a predictive model and conduct the sensitivity study to investigate the multiple factors on the performance of flow meter.

Funding

Only Home students can apply. Home tuition fees will be covered for the duration of the 3-year project.

The student will receive a standard stipend payment for the duration of the award. These payments are set at a level determined by the UKRI, currently £20,780 for the academic year 2025/26.
 

Specific requirements of the candidate

The qualifications, skills, knowledge and experience applicants should have for this project, in addition to our standard entry requirements.

Essential Criteria

• BEng/BSc/MSc in Mechanical Engineering, Applied Mathematics, Applied Mechanics, or related disciplines (a minimum honours degree at UK first or upper second-class level)
• Experience in computational fluid dynamic/finite element modelling by using commercial software such as Ansys, Abaqus, SolidWorks,etc.
• Fundamental knowledge in the fluid mechanics and solid mechanics
• Willing to travel and attend the meetings with industrial partners on site;
• Should have or willing to work within a multidisciplinary environment.

Desirable Criteria

• Experience of programme coding using commercial software such as Python or Matlab.
• Experience of parametric modelling.
• Evidence of good communication skills in both writing and oral such as presentation in the conference, publication in the peer reviewed journals.

Candidates are strongly encouraged to specifically address the essential criteria outlined in the Person Specification in their covering letter. 

As a PhD student, you will be expected to actively participate within the programme of study, showing good time management and organisation. You are expected to work upon and further develop initial research questions, completing tasks required to gain a PhD such as attending meetings, regularly reviewing literature, completing pertinent studies, disseminating research works/outputs at appropriate forums and writing a thesis on the topic.

How to apply

Interested applicants should contact Dr Jiling Feng for an informal discussion. 

To apply you will need to complete the online application form for a full-time PhD in the Department of Engineering.

You also need to include a standard CV and a covering letter of no more than two pages detailing how your experience and skills align with this project.

If applying online, you will need to upload your CV and covering letter in the supporting documents section or email the application form and the supporting documents to [email protected]. 

Closing date 1 December 2025. 

Expected start date April 2026.

Please quote the reference: SciEng-JF-April 2025-26-Coriolis Flow Meter

Project advert

Congenital Hyperinsulinism (CHI) is a rare inborn error of metabolism where the pancreas produces excessive insulin, resulting in persistently low blood sugar, leading to seizures and brain damage in newborn children. Our clinical partners at the Royal Manchester Children’s Hospital recognise that early diagnosis and prophylactic treatment with supplementary glucose substantially reduces brain damage during this critical post-natal period of neurodevelopment. Earlier diagnostic biomarkers of neurodegeneration in CHI could substantially accelerate diagnosis and treatment. At Manchester Met, we have developed a human ‘brain-on-a-chip’ model that faithfully recapitulates the neurovascular unit, where neurons interface with the vasculature in the brain. You will use CRISPR gene editing to introduce the most frequently occurring disease-causing mutation for CHI into induced Pluripotent Stem cells (iPSC). You will then be instructed in building the brain-on-a-chip model using iPSC to study the molecular mechanisms where genetic mutation, exposure to high insulin and low glucose combine to cause neurodegeneration in the brain. You will employ multiomic deep phenotyping to identify molecular alterations that relate to CHI and principally evaluate their fit as biomarkers for CHI diagnostics. This project will provide training in gene editing, iPSC technologies, and complex cell models with a focus on clinical unmet needs.

Project aims and objectives

The aim of this project is to comprehensively evaluate the combined effects of ABCC8 gene mutation, high circulating insulin and low circulating glucose to neurodegeneration in CHI.

Objectives:

1. Introduce CHI pathogenic mutations to the ABCC8 gene in iPSC using CRISPR gene editing.
2. Apply CHI iPSC to create a brain-on-a-chip model.
3. Evaluate individually and combinatorially the effects of ABCC8 mutation, high insulin and low glucose in causing neurodegeneration using the brain-on-a-chip model.
4. Conduct a transcriptomic and proteomic evaluation of CHI versus control conditions to identify putative biomarkers.

Funding

Only Home students can apply. Home tuition fees will be covered for the duration of the 3-year project.
 

The student will receive a standard stipend payment for the duration of the award. These payments are set at a level determined by the UKRI, currently £20,780 for the academic year 2025/26.
 

Specific requirements of the candidate

The qualifications, skills, knowledge and experience applicants should have for this project, in addition to our standard entry requirements.

Requirements include:

• A 1st or 2:1 degree in a relevant undergraduate degree.
• Experience of mammalian cell culture.

How to apply

Interested applicants should contact Prof Tristan McKay ([email protected]) for an informal discussion. 

To apply, you will need to complete the online application form for a full-time PhD (or download the PGR application form) in the Department of Life Sciences. 

Please include your CV and a cover letter addressing the project’s aims and objectives, demonstrating how the skills you have map to the area of research and why you see this area as being of importance and interest. 

If applying online, you will need to upload your statement in the supporting documents section, or email the application form and statement to [email protected]. 

Closing date: 16th December 2025

Expected start date: April 2026.

Please quote the reference: SciEng-TM-April 2026-Congenital Hyperinsulinism 

Project advert

In collaboration with the Aston Martin Aramco Formula One Team, we are offering a unique PhD opportunity to investigate how additive manufacturing waste streams can be recovered to retain original mechanical and material properties. This is an interdisciplinary project involving aspects of material science, chemistry, manufacturing, and life cycle assessment that feeds into the organisation’s sustainability strategy.

What you’ll do:

• Scope and categorise additive manufacturing waste in F1 motorsport to inform target waste streams with recycling potential.
• Develop solutions for AM waste as an alternative feedstock using chemical depolymerisation or other approaches.
• Explore opportunities to re-use material as an additive or filler product for other processes.
• Investigate sustainability implications and wider impact of developed processes.
• Develop a sustainability playbook for motorsport.
• Gain hands-on experience with state-of-the-art technologies, including stereolithography (SLA) printing at Aston Martin Aramco Formula One and Manchester Met’s PrintCity.
• Collaborate with experts in additive manufacturing, material science, sustainability and data science, producing impactful research publications while advancing knowledge at the intersection of engineering, sustainability and motorsport.

This project is highly relevant for candidates with a passion for material science, chemistry/chemical engineering innovation, advanced manufacturing and motorsport. If you are up for the challenge and want to join our team, apply now!

Project aims and objectives

The aim of this project is to develop an effective, sustainable solution for the recovery of waste material from additive manufacturing in motorsport applications. The objectives are:

1. Identify the waste streams and prioritise which should be targeted to ensure the maximum impact.
2. Develop a novel approach to recycling the material to enable the use of additively manufactured waste as an alternative feedstock.
3. Gain a deep understanding of the sensitivities, reliability and robustness of the novel solution.
4. Complete a Life Cycle Assessment related to the work.
5. Create a sustainability playbook for the recycling of waste streams in motorsport.

Funding

Only Home students can apply. Home tuition fees will be covered for the duration of the three-year and six-month award, which is £5,006 for the year 2025/26. 

The student will receive a standard stipend payment for the duration of the award. These payments are set at a level determined by the UKRI, currently £20,780 for the academic year 2025/26.
 

Specific requirements of the candidate

The qualifications, skills, knowledge and experience applicants should have for this project, in addition to our standard entry requirements.

We are looking for a highly motivated candidate with a strong background in Material Science, Chemistry, or a closely related field, with an interest in advanced manufacturing, design of experiments, and sustainability. The ideal candidate should meet some of the following specific requirements:

• A minimum of an honours degree at first or upper second class (2:1) level (or equivalent) in Material Science, Chemistry/chemical engineering, or Mechanical Engineering with a focus on sustainbaility, or a related discipline.
• A strong understanding of sustainability related to advanced manufacturing and/or chemical recycling of materials.
• Familiarity with research methodologies, including design of experiments and a basic knowledge of machine learning is an advantage. Experience in working with large datasets is highly desirable.
• Polymer degradation chemistry experience is highly desirable.
• Experience in UK laboratory safety.
• Excellent communication and teamwork skills, as the role involves collaboration with industry partners and interdisciplinary teams.
• A passion for motorsport, sustainability, and applied research.

This is an exciting opportunity for a candidate who is keen to push the boundaries of chemical engineering research and contribute to real-world applications in the motorsport industry.

How to apply

Professor Carl Diver ([email protected]) will lead the project as your Principal Supervisor. Dr. Edward Randviir ([email protected]) and Dr. Rachel Dunk ([email protected]) will act as your co-supervisors. You are encouraged to apply for this opportunity directly by following the steps outlined below, without an informal discussion. 

To apply you will need to complete the online application form for a full-time PhD in Engineering.

Please include a one-page cover letter and CV of no more than two pages addressing the project’s aims and objectives, demonstrating how the skills you have map to the area of research and why you see this area as being of importance and interest. 

If applying online, you will need to upload your statement in the supporting documents section, or email the application form and statement to [email protected]. 

Closing date: 4 January 2026

Expected start date: April 2026

Please quote the reference: SciEng-CD-April 2026-Aston Martin Waste

Project advert

In collaboration with the Aston Martin Aramco Formula One Team, we are offering a unique PhD opportunity to investigate how additive manufacturing parameters influence the aerodynamic performance of wind tunnel components in elite motorsport. This interdisciplinary project will develop a data-driven approach to understand and predict how process settings, build orientation, machine variability, and material properties affect dimensional accuracy and aerodynamic behaviour, ultimately improving the reliability of aerodynamic testing. The project combines additive manufacturing, data analytics and fluid dynamics to bridge the gap between manufacturing and aerodynamic testing, supporting the next generation of high-performance engineering. 

What you’ll do:

• Investigate the relationship between manufacturing parameters (build orientation, resin choice, post-processing) and aerodynamic performance in wind tunnel tests.
• Develop an integrated performance model linking process data, 3D metrology, and wind tunnel results, allowing for predictive insights into the impact of manufacturing deviations on aerodynamic performance.
• Gain hands-on experience with state-of-the-art technologies, including stereolithography (SLA) printing and wind tunnel testing at Aston Martin Aramco Formula One and Manchester Met’s PrintCity.
• Collaborate with experts in additive manufacturing, fluid dynamics, and data science, producing impactful research publications while advancing knowledge at the intersection of engineering and motorsport.

This project is highly relevant for candidates with a passion for advanced manufacturing, motorsport, and engineering innovation. If you are up for the challenge and want to join our team, apply now!

Project aims and objectives

The main aim of this project is to develop a data-driven, predictive framework for additive manufacturing that links process parameters, dimensional accuracy, and aerodynamic performance for high-precision components used in wind tunnel testing. The specific objectives are:

1. Investigate the impact of SLA process settings (build orientation, resin type, post-processing) on geometric fidelity and aerodynamic behaviour.
2. Develop an integrated performance model combining SLA process data, metrology, and wind tunnel results to predict manufacturing-induced aerodynamic deviations.
3. Explore machine-to-machine variability and evaluate how local and systemic errors affect part quality.
4. Enhance CAD-to-print workflows to capture and mitigate sources of manufacturing variation.
5. Provide recommendations for process optimization and compensation strategies to improve repeatability and accuracy in high-performance applications.

Funding

Only Home students can apply. Home tuition fees will be covered for the duration of the three-year and six-month award, which is £5,006 for the year 2025/26. 

The student will receive a standard stipend payment for the duration of the award. These payments are set at a level determined by the UKRI, currently £20,780 for the academic year 2025/26.
 

Specific requirements of the candidate

The qualifications, skills, knowledge and experience applicants should have for this project, in addition to our standard entry requirements.

We are looking for a highly motivated candidate with a strong background in Mechanical, Manufacturing or Automotive engineering, or a closely related field, with an interest in advanced manufacturing, design of experiments, or fluid mechanics. Familiarity with Finite Element Analysis (FEA), Computational Fluid Dynamics (CFD), and manufacturing process optimisation using machine learning is highly desirable. The ideal candidate should meet some of the following specific requirements:

• A minimum of an honours degree at first or upper second class (2:1) level (or equivalent) in Mechanical Engineering, Manufacturing or Automotive Engineering, or a related discipline.
• A strong understanding of additive manufacturing, particularly stereolithography (SLA), and/or fluid dynamics or aerodynamics.
• Experience with 3D CAD modelling, manufacturing and the ability to work with metrology equipment (e.g., 3D scanning, surface inspection).
• Familiarity with data analysis tools (e.g., MATLAB, Python, or similar) and basic knowledge of machine learning is an advantage. Experience in working with large datasets is highly desirable.
• Familiarity with research methodologies, including experimental design and data-driven modelling, ideally within the context of manufacturing or engineering research.
• Excellent communication and teamwork skills, as the role involves collaboration with industry partners and interdisciplinary teams.
• A passion for motorsport, high-performance engineering, and applied research.

This is an exciting opportunity for a candidate who is keen to push the boundaries of engineering research and contribute to real-world applications in the motorsport industry.

How to apply

Professor Carl Diver ([email protected]) will lead the project as your Principal Supervisor. Dr. Oliver Duncan ([email protected]) and Dr. Rashid Jamshidi ([email protected]) will act as your co-supervisors. You are encouraged to apply for this opportunity directly by following the steps outlined below, without an informal discussion. 

To apply you will need to complete the online application form for a full-time PhD in Engineering.

Please include a one-page cover letter and CV of no more than two pages addressing the project’s aims and objectives, demonstrating how the skills you have map to the area of research and why you see this area as being of importance and interest. 

If applying online, you will need to upload your statement in the supporting documents section, or email the application form and statement to [email protected]. 

Closing date: 4 January 2026

Expected start date: April 2026

Please quote the reference: SciEng-CD-April 2026-Aston Martin Motorsport 

Project advert

We invite applications for a fully funded, multidisciplinary doctoral project focused on understanding the mechanistic drivers of sarcopenia, the debilitating age-related loss of muscle mass and function. This research addresses a critical unmet health challenge by exploring a fundamental, underexplored mechanism: how the disruption of the body’s internal circadian clock drives progressive decline at the neuromuscular junction, the vital connection between nerve and muscle.

You will have a unique opportunity to work with a multi-disciplinary team of cell and molecular biologists, chemists and computational experts pioneering research using an advanced, optogenetically controlled human-based nerve-muscle model. Using functional, molecular and metabolomics technologies, integrated with machine learning (ML) and artificial intelligence (AI) workflows, the project aims to create a comprehensive molecular atlas and identify novel, translational biomarkers and therapeutic targets.

The successful candidate will work with the multidisciplinary academic team in the newly built Dalton Building, equipped with state-of-the-art facilities. You will join a vibrant and rich research environment, offering unparalleled training opportunities in advanced cell biology, omics platforms and computational technologies. Your academic journey and development will be supported by our Doctoral College, which creates a supportive and stimulating environment in which our students can thrive.

Project aims and objectives

The core aim of this project is to determine how age-related circadian dysregulation impacts neuromuscular function and muscle homeostasis. This will be achieved by the following objectives:

1. Establishing a co-culture system with rhythmic stimulation to model an aged phenotype, followed by mechanistic interrogation using comprehensive metabolomics, structural, and functional analyses.
2. Using machine learning and artificial intelligence systems to integrate complex datasets, identifying and validating core molecular targets.

Funding

Both home students and international students can apply. Only home tuition fees will be covered for the duration of the 3 years award, which is £5,006 for the year 2025/26. Eligible international students will need to make up the difference in tuition fee funding (Band 3 for the year 2025/26).

The student will receive a standard stipend payment for the duration of the award. These payments are set at a level determined by the UKRI, currently £20,780 for the academic year 2025/26.
 

Specific requirements of the candidate

The qualifications, skills, knowledge and experience applicants should have for this project, in addition to our standard entry requirements.

 Essentia criteria:

• A first or upper second (2:1) class honours degree in a relevant science discipline such as Biomedical Science, Cell Biology, Molecular Biology, Physiology or a related field.
• Strong theoretical and practical knowledge of fundamental molecular and cell biology techniques, in particular mammalian cell culture.
• Demonstrable curiosity and enthusiasm for interdisciplinary research.
• Excellent written and verbal communication skills.
• Ability to work independently, manage time effectively, and collaborate as part of a team.

Desirable criteria:

• Knowledge of the molecular basis of ageing, muscle physiology, or the circadian clock.
• Experience or strong interest in data science, machine learning, or bioinformatics.
• Exposure to high throughput ‘omics’ techniques, such as metabolomics.

How to apply

Interested applicants should contact Dr Adam Lightfoot for an informal discussion. 

To apply you will need to complete the online application form for a full time PhD in Biological Science

Please complete the Doctoral Project Applicant Form, and include your CV and a covering letter to demonstrate how your skills and experience map to the aims and objectives of the project, the area of research and why you see this area as being of importance and interest. 

Please upload these documents in the supporting documents section of the University’s Admissions Portal.

Applications closing date: 3 March 2026

Expected start date: Oct 2026.

Please quote the reference:  SciEng-AL-2025-26-Chrono Sarc AI

Project advert

We are constantly balancing different movement goals as we walk through the world – maintaining stability, moving efficiently, and perhaps hurrying to catch a bus! Suboptimal control of gait can lead to a trip or fall - a major cause of injury, loss of independence and mortality, particularly in older adults. This PhD studentship offers an exciting opportunity to explore how people trade off different movement goals during locomotion in complex environments across the lifespan, and how these choices may influence falls risk in older adults.

The successful candidate will join a multidisciplinary supervisory team passionate about using science to improve people’s lives. They will gain hands-on experience working with adult participants across a wide age range and develop expertise in advanced biomechanical data collection and analysis techniques (e.g. optical motion capture, inertial measurement, electromyography) in the state-of-the-art Institute of Sport laboratories at Manchester Metropolitan University. The project will also provide opportunities to design and deliver innovative movement-based interventions.

The student will be encouraged and supported to present their work at national and international conferences, publish in leading scientific journals, and take advantage of a wide range of training and development opportunities within an inclusive, friendly and dynamic doctoral community.

Project aims and objectives

The aim of this PhD project is to understand how people balance different movement goals such as stability, energy economy and speed when walking in challenging situations - and to explore whether this balance differs in people with a history of falls. The objectives are to determine the biomechanical, psychological and environmental factors that influence movement goal priorities, identify which adaptive walking tasks best reveal them, and test whether training or other interventions can shift how people prioritise different movement goals. The findings will support new approaches to improving balance and preventing falls.

Funding

Both Home and International students can apply. Only home tuition fees will be covered for the duration of the three year award, which is £5,006 for the year 2026/27. Eligible international students will need to make up the difference in tuition fee funding (Band 3 for the year 2026/27).

The student will receive a standard stipend payment for the duration of the award. These payments are set at a level determined by the UKRI, currently £20,780 for the academic year 2025/26.
 

Specific requirements of the candidate

The qualifications, skills, knowledge and experience applicants should have for this project, in addition to our standard entry requirements.

• Applicants will be expected to have a first or upper second class level degree (or equivalent) in a relevant subject (e.g. sports science, kinesiology, biomechanics, engineering, physiology, human biology, psychology, zoology) and a demonstrable interest in understanding human movement.
• Experience in human data collection would be desirable.
• Experience analysing movement using optical motion capture or inertial measurement systems would be desirable.
• Basic programming skills in Matlab or a similar language would be desirable; willingness to learn these skills is essential.

How to apply

Interested applicants should contact Dr Kat Daniels ([email protected]) for an informal discussion. 

To apply you will need to complete the online application form for a full time PhD in Sports & Exercise Science

Please complete the Doctoral Project Applicant Form, and include your CV and a covering letter to demonstrate how your skills and experience map to the aims and objectives of the project, the area of research and why you see this area as being of importance and interest. 

Please upload these documents in the supporting documents section of the University’s Admissions Portal.

Applications closing date: 4 March 2026

Expected start date: October 2026

Please quote the reference: SciEng-KD-2025-26-Adaptive Gait

Project advert

This PhD studentship aims to transform how exercise rehabilitation is delivered for working-age adults living with multiple long-term conditions (MLTCs). Partnering with Chiron AI, an NHS-compliant digital health company, the research project will develop and evaluate an AI enabled rehabilitation model that identifies individual needs and connects patients to the most appropriate exercise and support pathways across community and healthcare settings.

Working with key stakeholders across Greater Manchester, including the Strategic Clinical Network of Greater Manchester and Eastern Cheshire, the project will analyse regional health and activity datasets to inform inclusive, scalable models of care. The research will explore how AI-informed systems can improve access, engagement, and long-term outcomes, influencing both local practice and national policy.

Based within Manchester Met’s world-leading Institute of Sport, the doctoral researcher will join a dynamic interdisciplinary environment linking sport and exercise science, data analytics, and health innovation. This collaboration offers a unique opportunity to contribute to one of the UK’s most significant challenges—supporting healthier, more active working lives through intelligent, evidence-based rehabilitation. 

The student will benefit from a multidisciplinary team with specialists from academia, healthcare, and industry led by Dr Amy Harwood and will join a vibrant postgraduate community and research group. 

Project aims and objectives

The projects aim is to implement and evaluate AI-informed, scalable, integrated rehab for working-age adults with multiple long-term conditions across GM; and develop a framework to support national roll-out.  Specific research questions include:

1. How can multi-source health and activity datasets be leveraged to evaluate the AI-enabled rehabilitation platform that enhances the accessibility, inclusivity, and person-centred nature of rehabilitation services?
2. How does the implementation of such an integrated system compare with existing rehabilitation models in terms of uptake, healthcare resource utilisation, and patient outcomes, and what factors influence its long-term scalability and sustainability?
3. Does the app influence behaviour and determine sustainable healthy long-term behaviours and improve cardiorespiratory function?

Funding

Both Home and International students can apply. Only home tuition fees will be covered for the duration of the 3-year award, which is £5,006 for the year 2025/26. Eligible international students will need to make up the difference in tuition fee funding (Band 2 for the year 2025/26).

The student will receive a standard stipend payment for the duration of the award. These payments are set at a level determined by the UKRI, currently £20,780 for the academic year 2025/26.
 

Specific requirements of the candidate

The qualifications, skills, knowledge and experience applicants should have for this project, in addition to our standard entry requirements.

Essential:

• First or upper second class BSc honours degree in a relevant degree such as sport and exercise science, human physiology, data science
• Experience of working with patients with long-term health conditions
• Proficient in Microsoft office, specifically Microsoft excel
• Experience in working with digital health technologies

Desirable:

• MSc in clinical exercise physiology (or other relevant discipline)
• Evidence of engagement in research activities (e.g., managing a research project, publishing journal articles, conference presentations)
• Experience of using statistical and/or analytical software packages (e.g., SPSS, R, Tableau, Power BI, etc).
• Experience of coding

How to apply

Interested applicants should contact Dr Amy Harwood for an informal discussion. 

To apply you will need to complete the online application form for a full time PhD in Sports & Exercise Science

Please complete the Doctoral Project Applicant Form, and include your CV and a covering letter to demonstrate how your skills and experience map to the aims and objectives of the project, the area of research and why you see this area as being of importance and interest. 

Please upload these documents in the supporting documents section of the University’s Admissions Portal.

Applications closing date: 5 March 2026 

Expected start date: October 2026

Please quote the reference: SciEng-AH-2025-26- Access 4 All

Project advert

Entanglement distribution is a foundational capability for quantum networks, enabling diverse quantum technologies including—but not limited to—quantum key distribution (QKD). QKD provides information-theoretic security even against quantum-capable adversaries, making it one of the most mature and commercially relevant applications of quantum communication. 

However, current QKD links are limited to short distances. Overcoming this limitation requires quantum repeaters, which enable long-distance entanglement distribution and are therefore essential for building large-scale, secure quantum networks. Developing efficient, scalable, and physically realizable repeater-assisted architectures for entanglement distribution protocols remains a significant theoretical and practical challenge.

This PhD project will investigate optical quantum repeaters for long-distance secure QKD. You will develop theoretical frameworks to analyse repeater architectures, evaluating both amplifier-enhanced and memory-assisted protocols. Crucially, you will develop experiment-ready models that rigorously account for realistic device imperfections—bridging the gap between theory and practical implementation. 

Project aims and objectives

• Develop a generalised theoretical framework for quantum repeater architectures
• Investigate and compare specific QKD protocols; Model realistic device imperfections by incorporating loss, noise, and other experimental constraints into the theoretical analysis
• Provide design guidelines for future experimental implementations of quantum repeater networks, specifying hardware requirements and performance benchmarks
• Contribute to the development of large-scale quantum communication infrastructure by identifying viable pathways for practical deployment of secure quantum networks. 

Funding

Both Home and International students can apply. Only home tuition fees will be covered for the duration of the 3-year award, which is £5,006 for the year 2025/26. Eligible international students will need to make up the difference in tuition fee funding (Band 2 for the year 2025/26).

The student will receive a standard stipend payment for the duration of the award. These payments are set at a level determined by the UKRI, currently £20,780 for the academic year 2025/26.
 

Specific requirements of the candidate

The qualifications, skills, knowledge and experience applicants should have for this project, in addition to our standard entry requirements.

• First or upper second class (2:1) honours degree from a UK university or an equivalent qualification (or be close to completing) in Physics, Electrical Engineering, Computer Science, or a related discipline.
• Strong analytical and problem-solving skills, and the ability to work independently and collaboratively.
• Strong analytical skills and motivation for independent research are essential.
• Knowledge of optics and communications is desirable.
• Knowledge of quantum optics and quantum communications is desirable.
• Familiarity with programming (MATLAB, Python, etc.) is desirable.

How to apply

Interested applicants should contact Dr Masoud Ghalaii ([email protected]) for an informal discussion. 

To apply you will need to complete the online application form for a full time PhD in Computing & Digital Technology

Please complete the Doctoral Project Applicant Form, and include your CV and a covering letter to demonstrate how your skills and experience map to the aims and objectives of the project, the area of research and why you see this area as being of importance and interest. 

Please upload these documents in the supporting documents section of the University’s Admissions Portal.

Applications closing date: 8 March 2026

Expected start date: October 2026

Please quote the reference:

SciEng-MG-2025-26-Quantum Key Distribution

Project advert

Aspergillus fumigatus is a WHO-prioritised human fungal pathogen responsible for millions of infections worldwide, including life-threatening invasive aspergillosis and sight-threatening fungal keratitis. Despite its global impact, the genetic mechanisms that enable it to breach host barriers and cause tissue destruction remain poorly understood, leaving few effective treatment options and critical unmet clinical need.

This PhD offers a unique opportunity to explore the molecular basis of A. fumigatus pathogenicity using a pioneering kinome-wide knockout library to identify protein kinases critical for tissue invasion. The project combines functional genomics, advanced infection models, live-cell imaging, and drug discovery, providing a rare chance to connect fundamental biology with translational applications.

Students will join a collaborative, multidisciplinary environment, supervised by Dr Can Zhao at Manchester Metropolitan University, with support from external partners. Training will include cutting-edge laboratory techniques, bioinformatics, and scientific communication, while exposure to international collaborations and state-of-the-art facilities will prepare candidates for a wide range of research careers.

This PhD is ideal for a motivated, curious researcher eager to make a real-world impact, gain exceptional skills, and contribute to the development of novel therapies against a major global health threat.

Project aims and objectives

This PhD will identify the genetic drivers that enable Aspergillus fumigatus to invade human tissues, a critical factor behind its devastating impact on global health. Using a pioneering kinome-wide knockout library, the student will uncover protein kinases essential for tissue penetration, validating them through cutting-edge in vitro, ex vivo, and in vivo infection models. Selected targets will then be investigated for potential inhibition using advanced in silico and experimental drug discovery approaches.

By combining functional genomics, live-cell imaging, and translational models, this project aims to generate breakthrough insights into fungal pathogenesis. The findings have the potential to guide the development of novel antifungal therapies, directly improving patient outcomes and addressing a pressing global health challenge.

Funding

Home students can apply. Only home tuition fees will be covered for the duration of the award (3 years) which is £5,006 for the year 2025/26.

The student will receive a standard stipend payment for the duration of the award. These payments are set at a level determined by the UKRI, currently £20,780 for the academic year 2025/26.
 

Specific requirements of the candidate

The qualifications, skills, knowledge and experience applicants should have for this project, in addition to our standard entry requirements.

Applicants should hold (or be about to obtain) a minimum upper second-class undergraduate degree (or equivalent) in microbiology, molecular biology, or a related life sciences discipline. Research experience in microbiology, functional genomics, infection biology, or drug discovery is highly desirable. Candidates should have strong analytical and laboratory skills, and the ability to work independently within a collaborative team.

How to apply

Candidates must contact the primary supervisor (Dr Can Zhao) before applying to discuss their interest in the project and assess their suitability. 

To apply you will need to complete the online application form for a full time PhD in Biological Science

Please complete the Doctoral Project Applicant Form, and include your CV and a covering letter to demonstrate how your skills and experience map to the aims and objectives of the project, the area of research and why you see this area as being of importance and interest. 

Please ensure that your application also includes your Academic Certificates and Transcripts as supporting documents.

Please upload all documents in the supporting documents section of the University’s Admissions Portal.

Applications closing date: 20 March 2026 

Expected start date: October 2026

Please quote the reference: SciEng-CZ-2025-26-Fungal Invasion Insights

Project advert

This studentship offers an exciting opportunity to investigate how physical inactivity contributes to the development of type 2 diabetes and to explore whether simple lifestyle strategies can offset its negative effects on both metabolic and brain vascular health.

Based at Manchester Metropolitan University’s Institute of Sport, the successful applicant will join a multidisciplinary supervisory team and lead a human intervention study that combines real-world lifestyle monitoring with cutting-edge laboratory techniques, including MRI, glucose metabolism testing and cerebrovascular ultrasound.

This PhD provides a unique opportunity to develop a wide range of research and professional skills. The student will gain hands-on experience in human physiology, nutrition, data analysis and clinical research, while also engaging with diverse stakeholders across academic, clinical and community settings. The project’s multidisciplinary nature will support the development of technical expertise, collaborative working, and professional networking.

The candidate will be supported to publish high-impact scientific papers, present at national and international conferences, and benefit from extensive training and development opportunities within a vibrant, inclusive doctoral community. This PhD is ideal for a motivated and ambitious individual passionate about preventing chronic disease and contributing to future public health strategies with real-world impact.

Project aims and objectives

This project aims to investigate how short-term physical inactivity affects glucose metabolism, liver fat accumulation, mitochondrial function and brain vascular health in adults at risk of type 2 diabetes. The study will:

• Assess the physiological consequences of seven days of reduced movement on metabolic and cerebrovascular systems.
• Identify whether simple, achievable lifestyle adjustments can help prevent or reverse these effects.
• Explore the potential for rapid recovery of metabolic and vascular function once habitual activity levels are resumed.

By integrating real-world behaviour monitoring with advanced laboratory techniques, this project will generate essential evidence to support practical and scalable strategies for preventing metabolic disease.

Funding

Both Home and International students can apply. Only home tuition fees will be covered for the duration of the 3-year award, which is £5,006 for the year 2025/26. Eligible international students will need to make up the difference in tuition fee funding (Band 3 for the year 2025/26).

The student will receive a standard stipend payment for the duration of the award. These payments are set at a level determined by the UKRI, currently £20,780 for the academic year 2025/26.
 

Specific requirements of the candidate

The qualifications, skills, knowledge and experience applicants should have for this project, in addition to our standard entry requirements.

We are looking for a highly motivated and enthusiastic candidate with:

• A first-class or upper-second-class degree (or equivalent) in physiology, nutrition, biomedical science, exercise science or a related subject.
• A keen interest in human metabolism, physical inactivity, and diabetes prevention.
• Experience in laboratory-based research or human data collection is desirable.
• Strong communication, organisation and teamwork skills.
• A collaborative mindset and willingness to work across laboratory, clinical and community settings.

A relevant Master’s degree, experience with data analysis or engagement in public-facing research would be advantageous. We welcome applications from individuals with a passion for improving health outcomes through real-world lifestyle research.

How to apply

Interested applicants should contact Dr Kelly Bowden Davies for an informal discussion. 

To apply you will need to complete the online application form for a full time PhD in Sports & Exercise Science. 

Please complete the Doctoral Project Applicant Form, and include [your CV] and [a covering letter] to demonstrate how your skills and experience map to the aims and objectives of the project, the area of research and why you see this area as being of importance and interest. 

Please upload these documents in the supporting documents section of the University’s Admissions Portal.

Applications closing date: 10 March 2026 

Expected start date: October 2026

Please quote the reference: SciEng-KBD-2025-26-The STEPS Study