PhD topics for research students

Leukaemia is the most common childhood cancer, and growing evidence suggests it often begins before birth. Chromosomal translocations that create gene fusions are a hallmark of many leukaemias. Several are specific to paediatric disease, yet we still don’t fully understand how they form. Our early chromosome‑positioning work using fluorescence in situ hybridisation (FISH) shows that exposing leukaemia cells to different concentrations of synthetic vitamin B9 (folate) — which is essential for foetal blood cell development — can dramatically change the nuclear positioning of specific chromosomes that carry fusion‑prone genes. To build on this, we’ll investigate 3D genome organisation in more depth by examining how these fusion‑prone genes sit in relation to each other. Alongside FISH, we’ll use high‑throughput chromosome conformation capture (Hi‑C). Hi‑C will give us a detailed view of higher‑order chromatin architecture and help us assess how this structure might influence susceptibility to chromosomal translocations. We also plan to integrate these 3D genomics data with future epigenomic analyses to explore folate‑dependent changes in DNA methylation and how they may affect genome organisation and translocation risk.

This project aims to develop multifunctional novel bioactive tissue scaffolds using 3D printing, biomaterials science and controlled drug delivery systems to enhance tissue regeneration. Tissue scaffolds are 3D structures that mimic natural tissues’ architecture and support cell growth and differentiation. While tremendous progress has been made in developing scaffolds, developing tissue scaffolds for interfacial tissues such as osteochondral tissue is still challenging.3D printing, also known as additive manufacturing, continues to attract attention in the tissue engineering community for its flexibility and customisability. Compared to conventional manufacturing processes, 3D printing has the advantage of fabricating 3D constructs to produce personalised tissue engineering scaffolds with controllable complex geometries to directly match the natural tissue.Applicants will be required to demonstrate their experience in mechanical engineering, bioengineering, medical engineering, or any other related fields, understanding of engineering design, design optimisation, and engineering materials. Knowledge of experimental methods of using 3D printing is desirable. References Zhang, B., Huang, J. and Narayan, R.J., 2020. Gradient scaffolds for osteochondral tissue engineering and regeneration. Journal of Materials Chemistry B, 8(36), pp.8149-8170.Zhang, B., Guo, L., Chen, H., Ventikos, Y., Narayan, R.J. and Huang, J., 2020. Finite element evaluations of the mechanical properties of polycaprolactone/hydroxyapatite scaffolds by direct ink writing: Effects of pore geometry. Journal of the Mechanical Behavior of Biomedical Materials, 104, p.103665.Zhang, B., Gleadall, A., Belton, P., Mcdonagh, T., Bibb, R. and Qi, S., 2021. New insights into the effects of porosity, pore length, pore shape and pore alignment on drug release from extrusion based additive manufactured pharmaceuticals. Additive Manufacturing, 46, p.102196.

We are offering a self-funded PhD position with the Brunel Business School. The project focuses on addressing healthcare workforce challenges in an AI-enabled context. Applications are accepted on a rolling basis. If you have any questions about the project or would like to arrange an informal discussion, please reach out to Professor Julie Davies at julie.davies@brunel.ac.uk. The project Significant healthcare workforce shortages globally and increasing GDP expenditure on healthcare requires innovative multidisciplinary approaches to workforce development. We invite postgraduate researchers who are interested in understanding how practitioners navigate rapid changes in the healthcare sector for sustainable careers. Our project aims to conceptualise social capital and identity shifts in crafting careers with changes in technology, especially in AI-enabled workplaces. Here are some research questions you might consider: How do different learning trajectories affect healthcare worker careers? How is technology transforming the healthcare workforce? How does technology redraw knowledge boundaries amongst healthcare practitioners?• What drives workforce engagement and productivity in the healthcare sector? What effective career experiences can sustain meaningful healthcare careers? What creative methodologies are useful to gain insights into healthcare workforce development in collaboration with key stakeholders?

We are offering a self-funded PhD position addressing the challenge of energy losses in African power distribution networks through advanced loss reduction techniques with the Department of Electrical and Power Engineering. Applications are accepted on a rolling basis, so you can apply at any time. If you have any questions about the project or would like to arrange an informal discussion, please reach out to Dr Ahmed F. Zobaa at ahmed.zobaa@brunel.ac.uk. The project This research will focus on reducing energy losses in African power distribution networks, where both technical and non-technical losses are a significant issue. The study will examine advanced loss reduction techniques, including improved network design, real-time monitoring, and the use of distributed generation and energy storage systems. Case studies of high-loss regions will be used to identify root causes and propose tailored solutions that can be scaled across the continent. A cost-benefit analysis will assess the financial impact of loss reduction initiatives, offering practical strategies for improving the efficiency of Africa’s power distribution networks.

We are offering a self-funded PhD position in addressing water-energy nexus challenges in the Middle East through renewable energy integration with the Department of Electrical and Power Engineering. Applications are accepted on a rolling basis, so you can apply at any time. If you have any questions about the project or would like to arrange an informal discussion, please reach out to Dr Ahmed F. Zobaa at ahmed.zobaa@brunel.ac.uk. The project This research will tackle the pressing water-energy nexus challenge in the Middle East, where energy-intensive desalination processes require significant electrical power. The study will investigate the integration of renewable energy sources, such as solar and wind, into the power supply for desalination plants. By modelling and simulating various renewable energy configurations, the research will evaluate their technical and economic feasibility, aiming to reduce reliance on fossil fuels and improve the sustainability of water supply systems. Policy frameworks that promote investment in renewable energy for water and energy needs will also be examined.

This doctoral project will investigate the adoption and impact of emerging technologies—specifically blockchain and artificial intelligence (AI)—in emerging markets, focusing on how regulatory environments and institutional pressures shape innovation strategies across sectors like finance, healthcare, and supply chain management. While blockchain and AI offer transformative potential in enhancing transparency, automating processes, and driving data-informed decisions, organisations in emerging economies often face unique regulatory and infrastructural challenges that influence adoption rates and strategic approaches. The student will undertake a mixed-methods approach, combining qualitative case studies and interviews with quantitative data analysis to capture a comprehensive view of technology adoption trends and the effects of regulatory constraints. Quantitative analysis will involve examining large datasets on technology adoption, regulatory metrics, and economic indicators to identify statistical correlations and causal relationships. The research aims to quantify the impact of regulatory and institutional factors on innovation performance and explore how firms can leverage governmental cooperation to overcome barriers and foster sustainable adoption of these technologies. This project offers collaboration opportunities with technology firms, regulatory bodies, and policy think tanks, providing the student with access to industry data and regulatory insights. The ideal candidate should possess strong quantitative analysis skills, including experience with statistical software (such as R, Python, or SPSS) and a background in business strategy, innovation management, or a related field, along with a foundational understanding of blockchain and AI.

Medical imaging seeks to reveal the structures and activities inside the human body that are normally invisible behind other body parts such as skin and bones. With a wide range of imaging technologies such as radiography, magnetic resonance imaging, ultrasound, echocardiography and tomography, it has long been of great importance in clinical practices for measurement, identification, location and structural analysis of targeted organs, tissues or areas of abnormality. In this project, we will address the above problems of medical imaging using deep learning methods. You will have opportunities to gain experience with the industry-demanding deep learning technologies at different levels, from the conventional Convolutional Neural Network (CNN), U-Net and nnU-Net, to the more advanced Large Vision Models and Multimodal Models such as SAM and its variants. For over a decade, our group have been working in an extensive area of artificial intelligence and data science. Recent projects include medical imaging, bioimaging, biometrics, natural language processing, semantic video analysis, pattern recognition and computer graphics. We have received numerous research awards from international conferences, research institutions and professional organisations. We invite talented and hard-working candidates to join us for their PhD studies. The successful candidate will work in the Department of Computer Science at Brunel University London and will be supervised by Dr Yongmin Li, who specialises in artificial intelligence and its downstream applications in natural language processing, image processing, medical imaging and business management. For informal enquiries about the research, please email yongmin.li@brunal.ac.uk

We are offering a self-funded PhD position in advanced reactive power control strategies for hosting capacity enhancement in distribution networks with the Department of Electrical and Power Engineering. Applications are accepted on a rolling basis, so you can apply at any time. If you have any questions about the project or would like to arrange an informal discussion, please reach out to Dr Ahmed F. Zobaa at ahmed.zobaa@brunel.ac.uk. The project This research will explore innovative reactive power control techniques to tackle overvoltage issues and significantly boost hosting capacity in distribution networks. It will evaluate the deployment of advanced smart inverters equipped with features like volt-watt control and dynamic reactive current support, offering a superior alternative to conventional inverters for enhancing voltage stability and power quality. The development of hybrid passive filters will also be investigated to mitigate voltage stresses and lower costs. Comprehensive modelling and experimental validation will assess these control strategies under both grid-connected and islanded conditions, while a thorough cost-benefit analysis will ensure their economic viability for large-scale adoption.

We are seeking a highly motivated and creative PhD candidate to work on a collaborative project aimed at the identification of therapies for an inherited neurodegenerative disease, Friedreich’s Ataxia (FRDA). The aim of this project is to identify potential and novel targets for the development of therapeutic strategies in the disease. This novel project has great potential to provide insight into the molecular mechanisms of FRDA and inform future therapy development. Overview The PhD studentship in the Ataxia group will involve the identification and validation of novel targets for the treatment of FRDA using various molecular and cell biology approaches. The successful applicant is expected to meet the project aims and objectives in line with the proposed project plan. The candidate will work closely with the Principal Investigator, other researchers in the Ataxia group and internal/external collaborators and is expected to present and disseminate project findings to partners and the wider scientific community. The successful candidate will be supervised by Dr Sara Anjomani Virmouni. Informal enquiries can be made via email to Dr Sara Anjomani Virmouni (Sara.Anjomani-Virmouni@brunel.ac.uk). Eligibility The successful applicant should hold an undergraduate degree (first or upper second class) or equivalent qualification in biology, genetics, or a related discipline, with particular experience in molecular and cellular biology. A Masters qualification in a relevant area would be desirable. Experience in some of the following molecular biology techniques and in vitro approaches is essential: passaging transfection siRNA overexpression stable line generation cloning PCR qPCR western blot immunofluorescence staining and imaging

Traditional manual maintenance of pipelines which requires digging of ground to get access to pipelines is ineffective because of safety issues, high cost and limited human vision. Thus, serious faults are often missed in the pipeline which causes failures such as leaks in the system. This project aims to design and develop AI (Artificial Intelligence) enabled autonomous robots integrated with an intelligent sensing system for the non-disruptive inspection of utility and sewage systems. The applicant will be required to demonstrate his/her strong programming skills and experience in robotics (experimental, modelling and/or analytical experience), machine vision and machine learning algorithms, and CAD software such as Solidworks or equivalent. The applicant should be highly motivated, able to work independently as well as in a team, collaborate with others and have good communication skills.

Research Area This PhD sits at the intersection of usable privacy, AI agents, human-centred security, and web interaction design. The project will explore how users’ privacy intentions can be meaningfully captured, interpreted, and enacted across complex digital systems. The focus is on AI-mediated privacy decision-making, particularly in everyday web interactions such as cookie consent banners, data-sharing prompts, authentication flows, and other consent and authorisation mechanisms. This research extends established work in privacy-preserving protocols and usable security into the emerging domain of AI-mediated user agency. Building on foundations in IoT security standardisation (IETF ACE) and privacy-by-design principles, the project investigates how AI agents can operationalise user privacy preferences across heterogeneous web ecosystems while maintaining transparency and accountability. Project Description Modern web users are repeatedly asked to make privacy decisions—often under time pressure, cognitive overload, and through poorly designed interfaces. While regulations require transparency and consent, current mechanisms largely shift responsibility to users without offering meaningful support. This PhD will explore how AI agents can act as privacy mediators between users and web services by: Interpreting high-level user privacy intent expressed in natural language, preferences, or behavioural patterns Mapping these intents to concrete, enforceable configurations (e.g., cookie choices, consent settings, authorisation scopes) Dynamically adapting decisions across websites, services, and contexts Supporting user agency, understanding, and trust rather than replacing decision-making The research will investigate how such agents can operate ethically and transparently, balancing automation with user control. Concrete prototypes will address real web interaction scenarios, including: Consent flows and scope negotiation based on representative, real-world authorisation infrastructures such as OAuth/OpenID Connect Cookie consent management and third-party tracking configurations Cross-site privacy preference propagation Key research questions may include: How can user privacy intent be represented in ways that are both machine-actionable and human-understandable? How can AI agents negotiate consent decisions on behalf of users while preserving agency and accountability? What design patterns support trust, contestability, and explainability in privacy-aware agents? How can such systems scale across heterogeneous web ecosystems? Candidates are strongly encouraged to propose refinements to the research questions based on their interests and expertise. Relevant Prior Work The project builds on and is informed by prior work including:Karen Renaud, Cigdem Sengul, Kovila Coopamootoo, Bryan Clift, Jacqui Taylor, Mark Springett, and Ben Morrison. 2024. “We’re Not That Gullible!” Revealing Dark Pattern Mental Models of 11-12-Year-Old Scottish Children. ACM Trans. Comput.-Hum. Interact. 31, 3, Article 33 (June 2024), 41 pages. https://doi.org/10.1145/3660342 Manohar, A., Sengul, C., Chen, J. (2023). Inclusive Privacy Control at Home for Smart Health. In: Hayes, S., Jopling, M., Connor, S., Johnson, M. (eds) Human Data Interaction, Disadvantage and Skills in the Community. Postdigital Science and Education . Springer, Cham. https://doi.org/10.1007/978-3-031-31875-7_9 Sengul, C. and Kirby, A.A. RFC 9431: Message Queuing Telemetry Transport (MQTT) and Transport Layer Security (TLS) Profile of Authentication and Authorization for Constrained Environments (ACE) Framework. RFC Editor. [Online] https://www.rfc-editor.org/rfc/rfc9431.html. Why This Project Matters This work addresses a critical gap between privacy regulation, technical enforcement, and lived user experience. By moving beyond static consent mechanisms, the project aims to contribute to: More inclusive and accessible privacy controls Reduced cognitive burden for users Practical pathways for responsible AI deployment in everyday digital life Evidence-based alternatives to dark-pattern-driven consent design Bridging the gap between privacy regulation and technical implementation The outcomes are relevant to academia, standards bodies, regulators, and industry. Methods and Skills You Will Develop The project combines technical system-building with rigorous human-centred evaluation, and its methodological approaches will be tailored to the candidate's strengths. Technical Development may include: Agent architecture design with explainable reasoning components Protocol analysis and privacy-preserving configuration generation Browser extension or middleware prototype development Integration with existing consent management platforms Human-Centred Research will consider: Participatory design studies with diverse user populations Longitudinal evaluation of agent-mediated privacy decisions Trust and agency assessment frameworks Accessibility and inclusion-focused design iterations Interdisciplinary Analysis may include GDPR compliance verification and regulatory alignment. What We Are Looking For We are looking for a motivated, self-funded PhD candidate with: A strong background in Computer Science or a closely related discipline Interest in privacy, security, AI, and human-centred computing Willingness to engage with interdisciplinary perspectives Particularly valuable backgrounds include: Web security and authentication protocols AI/ML with focus on transparency or explainability User experience research in security-sensitive contexts Policy or regulatory analysis in digital rights Accessibility and inclusive design Strong candidates will demonstrate curiosity about socio-technical challenges and commitment to research that serves diverse populations. Supervision and Research Environment The PhD will be supervised within Brunel's Computer Science for Social Good Research Group and the Centre for Artificial Intelligence: Social and Digital Innovation. The student will benefit from: Expertise in privacy-preserving protocols, IoT security, and AI governance Engagement opportunities with EPSRC research networks (e.g., SPRITE) Connections to standards bodies (IETF) and policy communities Collaborative environment emphasising responsible innovation and social impact Opportunities for interdisciplinary engagement across CS, HCI, and digital regulation The project draws on supervisory expertise in: Privacy-preserving protocol design and standardisation AI governance and responsible AI deployment Secure authentication and authorisation mechanisms Human-centred system design for social good The supervisory approach emphasises student agency, iterative feedback, and professional development beyond technical contributions, including publication strategies, networking, and career preparation. Funding and Practicalities This is a self-funded PhD position. Applicants should ensure they can cover tuition fees and living costs for the duration of the programme. Informal enquiries are strongly encouraged prior to application to discuss project fit, expectations, and potential refinements to the research questions. Please contact Dr Cigdem Sengul (Cigdem.Sengul@brunel.ac.uk).

The “AI Futures: Companionship, Connection, and Careers” project investigates how artificial intelligence—particularly in the form of companion technologies—is reshaping emotional, social, and professional landscapes. From digital assistants that support mental health, to AI-driven career mentors, to virtual companions that mitigate loneliness among young and ageing populations—this project explores the human consequences of an increasingly intelligent and relational digital world.In a time when traditional support systems are eroding and career pathways are becoming more volatile, AI companionship offers both promise and peril. We aim to map out these dynamics through critical inquiry, creative methods, and a commitment to inclusive innovation. I welcome PhD proposals in areas including (but not limited to): • AI Companions and Youth Transitions into Work. How might AI-based tools serve as mentors, guides, or companions for young people navigating precarious labour markets? What ethical boundaries must we consider? • Designing Empathetic Systems What design frameworks are needed to build relationally intelligent systems that support emotional wellbeing without reinforcing dependency or bias? • AI, Loneliness, and Marginalised Communities How can AI companionship help reduce social isolation among groups that are often excluded from mainstream digital innovations—such as disabled youth, elderly migrants, or NEET populations? • Digital Trust and Social Capital in AI-Mediated Interactions How do users come to trust (or reject) AI companions, and what social norms emerge from these relationships? • Algorithmic Intimacy and the Future of Care Work To what extent can AI replicate or enhance care roles traditionally filled by humans, and what are the implications for care economies and gendered labour? Sample Research Questions • In what ways can AI companionship promote meaningful learning and employability among youth? • How do users emotionally interpret the “presence” of an AI companion over time, and how does this shape identity and agency? • What new ethical dilemmas arise when AI systems are designed to simulate empathy, attention, or friendship? • How can we safeguard mental health and autonomy while fostering beneficial human-AI relationships? • What frameworks or policies could ensure equitable access to AI companionship technologies across socio-economic boundaries? Methodological Innovation Encouraged We welcome proposals that use creative, mixed, or longitudinal methods such as: • Ethnographic studies of AI use in everyday life • Co-design workshops with young people or marginalised communities • Reflective diaries on emotional engagement with AI over time • Experimental designs comparing human and AI social interactions • Critical design/speculative futures research What Student Will Gain Interdisciplinary Learning Environment: You will be part of a vibrant research community spanning Information Systems, Digital Sociology, Psychology, and Human-Computer Interaction. You’ll benefit from research clusters focusing on AI ethics, social innovation, and digital wellbeing. Opportunities for Policy and Industry Impact: The project is designed with a strong impact focus, enabling you to contribute to policy recommendations, prototype evaluations, or pilot interventions that support more inclusive and ethical AI deployments.

In today’s competitive market, creating a distinctive and memorable brand is more important than ever. Advances in artificial intelligence (AI) are transforming corporate brand design, enabling companies to create personalised, dynamic visual identities that resonate with consumers on a sensory level. This project aims to explore how AI can be integrated into corporate brand design to enhance visual identity and sensory engagement, ultimately influencing consumer perception, behaviour, and loyalty. The research will investigate how AI-driven branding strategies can create impactful visual identities, focusing on the following key areas: AI in visual identity development: Explore how AI can be used to design adaptive logos, colour schemes, and brand imagery that respond to consumer preferences and cultural contexts. The student will analyse how AI-driven design tools can produce cohesive and consistent brand visuals that maintain brand recognition while adapting to various consumer touchpoints. Personalised sensory branding: Examine the role of AI in sensory branding, such as tailoring visual, auditory, and even olfactory brand elements to enhance the consumer experience. This includes studying how AI-driven tools can create personalised and memorable sensory experiences that deepen consumer-brand connections. Influencing consumer behaviour through AI-enhanced brand design: Investigate how AI-driven visual identity elements influence consumer behaviour and purchasing decisions. The student will look at factors such as emotional response to brand visuals, brand loyalty, and the impact of adaptive brand designs on consumer engagement. Dynamic brand engagement across platforms: Assess how AI can help brands create seamless, visually appealing, and consistent identities across digital and physical platforms. This includes exploring the role of AI in generating real-time, personalised brand visuals on websites, apps, and social media to maintain cohesive brand perception. AI and brand authenticity: Consider the ethical implications and consumer perceptions of AI-driven branding, particularly around authenticity and transparency. This area will explore consumer attitudes toward AI-generated brand elements and how they influence trust and loyalty. Research approach The student will employ a combination of qualitative and quantitative methods, including case studies of brands using AI-driven design, consumer surveys on sensory branding, and interviews with branding professionals. Experimental studies may also be conducted to measure consumer responses to AI-generated visuals and sensory experiences, analysing factors such as engagement, brand recall, and purchasing intent. Expected background Candidates should have a background in branding, design, or marketing, with knowledge of AI applications in creative fields being advantageous. An understanding of consumer behaviour theory, sensory marketing, and visual identity will also support the project’s objectives. Analytical skills for interpreting data from consumer studies will be essential.

Libraries around the world digitise the historical handwritten documents to preserve historical past and educate the people about the cultural heritage. However, a reliable optical character recognition (OCR) algorithm is necessary to accurately capture massive historical handwritten documents available from various archives.Thus, this project aims to develop a reliable optical character recognition (OCR) algorithm based on deep learning techniques that can accurately capture handwritten text.

We are offering a self-funded PhD position in marketing with the Brunel Business School. The project focuses on AI-driven branding for sustainable development. Applications are accepted on a rolling basis. If you have any questions about the project or would like to arrange an informal discussion, please reach out to Dr Pantea Foroudi at pantea.foroudi@brunel.ac.uk. The project As artificial intelligence transforms industries, its role in branding offers an opportunity to advance sustainable practices, influence consumer behaviour, and even impact health and wellbeing. This project will explore how AI-driven branding and marketing can support the United Nations Sustainable Development Goals (SDGs), particularly those related to health, responsible consumption, and ethical practices. The research will focus on several interrelated topics at the intersection of branding, AI, health, and sustainability: Promoting health-conscious consumer behaviour: Investigate how AI can be used in branding to encourage health-conscious choices among consumers. This area will explore AI-driven personalisation strategies that suggest healthier product alternatives, monitor lifestyle choices, or provide insights into sustainable and health-focused brands. The student could examine the effectiveness of AI-driven nudges that promote choices aligned with both personal health and environmental goals. AI and mental health in brand engagement: Examine the psychological effects of AI-driven branding and its influence on consumer wellbeing. This topic will consider how brands can use AI to foster positive mental health outcomes by creating supportive, inclusive brand communities, or minimising harmful digital interactions. This area may include research into how brands can avoid creating addictive engagement patterns and instead foster meaningful, balanced connections with consumers. AI-powered health and wellness tracking: Explore the integration of AI with health data to create branded experiences focused on wellness and preventive health. For instance, wearable devices or apps that monitor fitness, nutrition, or stress levels can be linked to brands that encourage a healthier lifestyle. The student will analyse how this data can ethically and responsibly enhance brand loyalty while maintaining privacy. Responsible AI in health and fitness marketing: Evaluate the ethical implications of AI in promoting health and fitness brands, focusing on data privacy, transparency, and the avoidance of manipulative tactics. This topic will investigate guidelines and best practices for using AI to influence health-related choices without compromising consumer autonomy or wellbeing. AI, health literacy, and consumer education: Consider how AI can support health literacy by creating branded content that educates consumers on sustainable health practices, such as balanced diets, exercise routines, or eco-friendly wellness products. AI-driven content personalisation could make health information more accessible, addressing different demographics’ needs and promoting well-informed consumer decisions. AI and public health campaigns for sustainable behaviour: Explore how AI-driven branding can collaborate with public health initiatives to promote sustainability-focused behaviour. This topic would analyse how brands can work with health organisations to create campaigns that encourage behaviours like reduced sugar intake, waste reduction, or choosing eco-friendly products, thereby supporting health and sustainability goals simultaneously. AI-enhanced personalisation for sustainable health products: Assess how AI can personalise recommendations for sustainable health products, such as organic foods, non-toxic beauty products, or eco-friendly supplements. The student will study how AI can support brands that promote sustainable health products, understanding the factors that influence consumers’ choices in this area. AI and wellness in workplace health programmes: Research how AI-driven branding and marketing can support brands that promote workplace health and wellbeing.

In an increasingly digital and interconnected world, brands are exploring AI-driven strategies to engage consumers, shape brand perception, and drive sustainable practices. This project seeks to examine how AI-powered branding can foster sustainable consumer behaviour and contribute to achieving the United Nations Sustainable Development Goals (SDGs). Building on concepts from branding, digital marketing, and sustainability, this research will explore the potential of AI in creating personalised, responsible branding strategies. The selected student will investigate how AI can drive sustainable consumer choices by analysing digital interactions, creating adaptive marketing content, and promoting transparency in the supply chain. The research will also examine how AI can support brands in addressing SDGs, particularly those focused on responsible consumption, climate action, and economic growth. The potential research questions for the project are: How can AI-driven branding strategies influence sustainable consumer behaviour and promote responsible consumption in alignment with the United Nations Sustainable Development Goals (SDGs)? What specific AI tools and technologies are most effective in fostering brand transparency and trust among consumers concerned with sustainability? In what ways can AI-driven personalisation and adaptive marketing content encourage consumers to make eco-conscious choices? How do consumers perceive AI-driven branding initiatives, particularly those focused on sustainability, compared to traditional branding strategies? What ethical considerations must brands address when using AI to drive sustainable consumer behaviour, and how do these affect consumer trust and brand loyalty? How can AI support brands in promoting sustainable supply chain practices, and what impact does this transparency have on consumer behaviour? To what extent can AI-driven branding campaigns help brands achieve specific SDGs related to climate action, responsible consumption, and economic growth? What challenges do brands face in implementing AI-driven branding for sustainability, and how can these be addressed to optimise effectiveness? How do consumers’ digital interactions with AI-driven content affect their long-term commitment to sustainable consumption? What role can collaboration between AI firms, branding agencies, and sustainability advocates play in advancing AI-driven, sustainable branding practices? The student will conduct both qualitative and quantitative research, including data analysis of consumer interactions with AI-driven content, interviews with branding and marketing professionals, and potential case studies of brands leading in sustainability. Opportunities for collaboration with industry stakeholders, such as AI firms and branding agencies, may provide practical insights and access to innovative tools. Expected background Candidates should have a strong foundation in branding, marketing, or business studies, with knowledge of AI applications or digital marketing strategies being advantageous. An understanding of sustainable development and SDG frameworks will also support the project’s goals. The ideal candidate will possess analytical skills for data interpretation and be comfortable with interdisciplinary research.