Research clusters
Just AI Lab
Artificial Intelligence (AI) – including autonomous systems, machine learning, and other data-driven smart systems – are increasingly taking on crucial roles in many contexts, including health and wellbeing, tourism and leisure, security, law, human resources and education. Often, the humans who interact with and use these systems have a limited understanding of how they work, and consequently how they arrive at the judgements and decisions they output, with important consequences for trust in outputs and understandings of uncertainty.
Against this backdrop, the core purpose of the Just AI Lab is the just transition to socially just, trustworthy, responsible, open, inclusive and sustainable AI through impactful mission-oriented interdisciplinary research. For the transition to be just, we must understand, use, and engage critically with AI in all aspects of human endeavour. Through Just AI, we embrace the vision of the Scottish AI Strategy of a fairer, greener, more prosperous, and outward looking Scotland. Our key areas of interest are: Just Wellbeing, Just Work, Just Services, and Just Commerce and Just Governance.
Example projects
The example projects below are intended to inspire thought and provide context, but you are expected to submit an original project proposal that aligns with the research cluster.
- How can the regulation of AI and AI-generated decisions / outputs ensure the just transition to AI and its use to tackle societal challenges e.g. climate justice, social justice, etc.?
- How to deal with uncertainty, trust, and ethical design principles for transparent automated decision-making within selected domains such as organisational behaviour, governance, administration?
- How to develop and test AI tools to enhance healthy life choices for psychological and physical wellbeing?
Express your interest
Environmental monitoring for a more just and healthier world (EnvMo4All)
Social, economic and health challenges in Scotland and Worldwide can only be addressed with vital, trustworthy evidence. Environmental monitoring using sensors deployed on the ground or on-board satellites and other platforms (e.g., drones) can show objectively the state of matters, helping to inform and motivate achieving Sustainable Development Goals for a more just and healthier world. Sensors are not just useful to environmental modellers, but they are critical to evidence-based approach to shaping environmental and public health policies/management and provide important evidence to decrease mis-information and communication disruption.
In order to drive our society toward a brighter future, in this cluster we will work on research questions addressing the interface between data and people in Scotland and Worldwide. An example of our group interest is gathering evidence on climate change impacts encourage more accurate public perceptions and provide effective communications to counter biased perceptions and motivate support for action. Also, monitoring the environment can provide important intelligence when it comes to human health (e.g., pollution, vector-borne disease). The dissemination of this intelligence to local communities is often impacted by issues related to language, accessibility, social inequalities, sharing of ideas and colonisation attitudes. We will investigate how best to co-design the way this knowledge is created and shared, so that we can maximise its use and thus positive health and environmental impacts.
Example projects
The example projects below are intended to inspire thought and provide context, but you are expected to submit an original project proposal that aligns with the research cluster.
- Can satellite data monitoring floods and melting ice be used to motivate climate change action among the public and decision makers?
- Using real time data to provide the evidence to shift behaviours to improve water quality and mitigate impacts of extreme events.
Express your interest
4Spike: Smart Solutions with Structure and Sparsity (4SP) for Innovation and Knowledge Exchange
Rapid advances in data collection and transmission capacity mark the advent of the data age and prompt calls for a reinvention of signal processing system design and methods of data analysis. Since exponential functions are one of the fundamental objects in describing signal models, it is not surprising that their analysis plays a crucial role in several key enabling technologies. On top of this, newly developed technologies need to meet the requirements in different applications. Therefore, our cluster joins computational mathematicians and experts from identified research fields. By employing the latest advances in exponential analysis, we have been participating in the development of high-resolution radar imaging, 6G non-terrestrial networks, and antenna position estimations from an Unmanned Aerial Vehicle, commonly known as a drone. Currently, we are collaborating with South Africa’s antenna system design team for the Mid-Frequency Aperture Array (SKA-Mid) of the international radio telescope project Square Kilometre Array (SKA). We are part of an EU-funded Research and Innovation Staff Exchange consortium (EXPOWER) that has 18 members (3 research institutes, 8 universities, 7 companies) from 9 countries.
Our cluster offers PhD projects for research questions that require inter-faculty co-supervision. The participation of international and industrial partners will help to ensure the research impact. Now we seek to develop novel computational methods for extracting information from tissue measurements such as the magnetic resonance signal and other types of medical data. Our cluster has experts in physiology, nutrition, and metabolism, especially in relation to human tissue, such as muscle, fat, and the influence on health and athletic performance. Internationally, we collaborate with researchers from NIH (USA) and the University of Delaware (USA). Our industrial partner Virtonomy is a German company aiming at the development of a virtual trial platform to support medical device development and “digital twin”. Additionally, we plan to explore new applications in financial mathematics, for example, via the connection between exponential analysis and time series analysis. We aim to improve our ability to analyse multi-dimensional quasi-periodic or nonstationary time series, to detect economic trends, and to model credit risk. In this topic, we will collaborate with the Regulatory Credit Risk Modelling Team of ING Belgium and the Credit Risk Model Validation Team of KBC Bank NV Branch Bulgaria.
Example projects
The example projects below are intended to inspire thought and provide context, but you are expected to submit an original project proposal that aligns with the research cluster.
- Super-resolution nonlinear parameter estimation for tissue data analysis. Can we come up with a smart solution for tissue analysis and modelling? Is it possible to extract information on heterogeneity from sparse tissue measurement data?
- Multivariate time series analysis and forecasting applications in financial markets. How to take advantage of the progress in multivariate exponential analysis for financial time series analysis? Can we develop smart forecasting methods that are based on the latest results of non-stationary time-frequency analysis?
Express your interest
Applications of Behavioural Science to societal challenges and organisational strategy
Behavioural Science is a diverse and inherently multidisciplinary field that studies individual decision making and its translation into economic, commercial, social, and policy outcomes. To understand the full complexity of human behaviour, behavioural scientists synthesise theories, concepts, and methodologies across several disciplines such as economics, psychology, social science, philosophy, and health sciences. Behavioural Science is playing an increasing role in public policy, and it is raising new questions about fundamental issues – the role of government, freedom of choice, paternalism, and human welfare. Around the world, public officials are using behavioural findings to combat serious problems such as poverty, air pollution, highway safety, COVID-19, discrimination, employment, climate change, occupational and public health, to name just a few.
The aim of the Stirling Behavioural-Science Cluster is to develop innovative and practical solutions to real-world problems by identifying biases in human judgment and decision making; developing behaviourally informed interventions that can help improve decisions; performing empirical evaluations of said interventions; and providing the evidence base to enhance institutional and organisational design as well as policy making. Methodological and theoretical training will be across disciplines covering quantitative and qualitative skills and theoretical understanding aiming to prepare the future behavioural scientist for academic and non-academic roles. We welcome applications for PhD studentships across the following research themes:
Behavioural Health (e.g., healthy ageing, self-management & health behaviours, occupational health, pandemic responses, medical adherence)
Environmental Behaviour (e.g., climate change, societal support for net-zero policies, energy use, investment in energy efficiency, transport use)
Social and Political Behaviour (e.g., poverty, inequality, discrimination, voting, fairness, charitable giving, honesty, trust, crime prevention, happiness, and wellbeing)
Organisational Sustainability (e.g., organisational behaviour, responsible business, upskilling and education for sustainability)
Behavioural Finance (e.g., undersaving for retirement, over-/underinsurance against risks, poor investment decisions)
Market Behaviour (e.g., behavioural biases in economic exchange, behavioural consumer protection, market regulation)
Philosophy of Behavioural Science (e.g., ethics of behavioural interventions, freedom of choice, paternalism, risk communication)
Example projects
The example projects below are intended to inspire thought and provide context, but you are expected to submit an original project proposal that aligns with the research cluster.
- Cutting energy use and insulating homes: Why is the UK lagging behind?
- Nudging tissue donation and transplantation: Evidence from a quasi-experiment.
- Behaviour change in physical activity in later life: Is it ever too late?
- Why populism is popular: Keeping it simple in a complex world.
Express your interest
Innovative Approaches to Harm Reduction and Health Policy
Research in this cluster will explore innovative approaches to harm reduction and health policy, with a key focus on drugs, alcohol, tobacco and gambling. Globally, markets for these commodities are changing rapidly, and policymakers often struggle to keep pace with developments. While innovative policy responses are emerging – ranging from hi-tech controls on online gambling to the legal regulation of cannabis – these can often hit roadblocks, whether through commercial influence, political inertia, lack of resources or public scepticism.
This interdisciplinary cluster will seek to better understand how policymakers can innovate effectively to promote better health outcomes, and how innovative policies can be better evaluated. It will consider issues such as the systemic and political barriers to innovative health policy design and implementation; how effective policy ‘learning’ can be encouraged between different settings and across different health themes; how policy influence works, especially when driven by commercial interests; how to develop effective tools to improve policy implementation and evaluation; how policy innovations in the Global South can help implement World Health Organisation strategies to tackle non-communicable disease; and what practical strategies we can develop to promote effective innovation in these areas.
Example projects
The example projects below are intended to inspire thought and provide context, but you are expected to submit an original project proposal that aligns with the research cluster.
- Innovative approaches to cannabis regulation: how is policy learning being applied?: To what degree are those jurisdictions currently adopting innovative approaches to cannabis regulation, including the establishment of legal markets, applying policy lessons from the experience of tobacco and alcohol regulation? Are new examples of regulatory good practice emerging? How (if at all) is commercial influence in policymaking being addressed? What should the measures of policy success be in this area?
- How do rolling tobacco smokers respond to innovative tobacco control policies?: How do rolling tobacco smokers in the UK respond to novel policies such as standardised packaging, new label warnings, health-promoting inserts and warnings printed on cigarette sticks. This PhD would apply a mixed-methods approach using both a longitudinal dataset and qualitative research.
- Innovative alcohol policy in the Global South: How are innovative policies to reduce the harmful use of alcohol in the Global South currently being implemented, particularly around marketing, pricing, availability, or drink-driving? What evidence exists around alcohol industry activity in the policy making process?
Express your interest
Digital Health Technology and Behavioural Science
Research question: Digital technologies have become part of everyday life for most people and innovation in the digital sphere is happening fast. The capacity for technology to improve health and wellbeing outcomes is substantial. Therefore, research in the field of digital health needs to incorporate multiple disciplines to be able to address relevant societal challenges. The overall purpose of this cluster is to address the needs of society through innovation and interdisciplinary research by addressing two main challenges.
- Digital technology is too often employed as a simple fix, transferring existing services/tools or resources into a digital format, frequently a digital application, with limited consideration of other more appropriate technologies that may be better at facilitating health outcomes.
- The technology is often developed and evaluated without having the actual user of the technology in mind. Little attention is paid to the behaviour change required of the user and the barriers and facilitators of its use. Thus, questions around what is working, why it is working, who it is working for and where there may be incidental harm by, for example, widening the digital poverty gap, can be neglected. Digital health in different cultures and nations demonstrates that technology use may be culturally specific and may be influenced by affordability, customary practices, family roles, network coverage and digital literacy, and other factors influencing their acceptability by its users. Similarly, issues of trust and communication also infiltrate the uptake of digital solutions.
Impact: This cluster will enhance our understanding of the development and design of digital technology for its use in health promotion, diagnosis, management, and prevention, taking into consideration psychological and behavioural, social, cultural, economic, political and environmental contexts. The strengths of the management and supervisory team for this IAS PhD studentship cluster is that supervisors are from several disciplines with extensive experience in all aspects of digital health and its applications. Involving stakeholder and co-developing research studies and digital interventions will support the scalability and translation of the research in this cluster. PGRs in this cluster will be particularly well-trained in interdisciplinary research and contexts and, therefore, will be able to work and lead in a range of fields after finishing their PhD.
Example projects
The example projects below are intended to inspire thought and provide context, but you are expected to submit an original project proposal that aligns with the research cluster.
- Co-developing and evaluating digital interventions that target health-related behaviours.
- Co-developing and using digital technology to improve medical diagnosis.
Express your interest