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Infrastructure and Environment
Advanced electronic/optoelectronic technologies designed to allow stable, intimate integration with living organisms will accelerate progress in biomedical research; they will also serve as the foundations for new approaches in monitoring and treating diseases.
Log jams — accumulations of floating wood in rivers — play a critical role in shaping fluvial landscapes, influencing flood dynamics, sediment transport, and aquatic ecosystems. Despite their ecological and hydraulic importance, we still lack a predictive, mechanistic understanding of how individual logs interact to form stable jams, how these structures resist or yield to flow, and how changes in geometry or hydrodynamic forcing drive transitions between clogging and release. This project will address these questions using particle-based computational simulations of log jam formation and deformation under flow. You will develop and apply numerical tools to represent logs as interacting elongated particles within a fluid environment, capturing contact, friction, buoyancy, and hydrodynamic drag. By systematically varying log aspect ratio, size distribution, and flow conditions, you will identify the micro-mechanical origins of jam stability and quantify the conditions under which logs transition between mobile, jammed, and partially clogging states. Through this work, you will develop expertise in large-scale particle-based simulation, computational fluid dynamics, and the physics of granular and particulate systems. You will learn to extract effective rheological and mechanical properties from microscale simulations, linking particle-scale processes to river-scale behaviour. The results will inform predictive models for log jam formation and stability, with implications for flood risk management, river restoration, and the design of nature-based engineering solutions. This PhD project will be supervised by Dr Chris Ness (School of Engineering, University of Edinburgh) and will involve collaboration with academics from partner institutions. Interested candidates are encouraged to contact the supervisor for more information (chris.ness@ed.ac.uk).
Website: https://christopherjness.github.io/ Contact: Dr Christopher John Ness(Chris.Ness@ed.ac.uk)
Minimum entry qualification- an Honours degree at 2:1 or above (or international equivalent) in a relevant science or engineering discipline, possibly supported by an MSc Degree
Further information on English language requirements for EU/Overseas applicants.
Applications are welcomed from self-funded students, or students who are applying for scholarships from the University of Edinburgh or elsewhere as well as self-funded students.
Funding Eligibility - Home applicants only (UK+EU settled/pre-settled)
Funding may be available for this project.
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Suspensions of particles in liquid are found throughout nature and industry, for instance slurries, mudslides, chocolate, toothpaste, and ceramics. Understanding their flow properties is crucial to characterising engineering processes and describing the natural world. We are just beginning to unravel the dramatic influence that stress-controlled particle-particle interactions have on the flow behaviour when the liquid is Newtonian and the particles are hard, spherical and roughly monosized [1]. In reality these conditions are rarely met: particles are usually irregular, being elongated and having a broad size distribution, while suspending liquids are often ‘viscoelastic’. A crucial scientific question is: how do the combined microphysics of these particle-level details control the resulting flow behaviour? For many scenarios in the natural world and in industry, answering this question is key to engineering design and natural hazard mitigation. • You will address this question using predominantly computational means, developing expertise in particle-based simulation, high performance computing, and data analysis; • You will become an expert in rheological characterisation of complex fluids; • Building upon codes developed in Edinburgh, you will implement particle-shape models to simulate bulk flow of suspensions of elongated particles. • You will develop post-processing techniques to generate viscosity and microstructural measurements; • Your work will improve our fundamental understanding and guide constitutive model development. • You will gain real-world experience by collaborating with our industrial partners on a contemporary engineering challenge. This computational project is supervised by Dr Chris Ness (School of Engineering, University of Edinburgh) and will involve regular interaction with experimentalists from academia and industry. Interested candidates may contact the supervisor for further information (chris.ness@ed.ac.uk).
Website: https://christopherjness.github.io/ Contact: Dr Christopher John Ness(Chris.Ness@ed.ac.uk)
[1] Ness, Christopher, Ryohei Seto, and Romain Mari. The physics of dense suspensions, Annual Review of Condensed Matter Physics 2022, 13:97-117 You can read more about the scientific work of my group here: https://christopherjness.github.io/papers
Minimum entry qualification- an Honours degree at 2:1 or above (or international equivalent) in a relevant science or engineering discipline, possibly supported by an MSc Degree
Further information on English language requirements for EU/Overseas applicants.
Applications are welcomed from self-funded students, or students who are applying for scholarships from the University of Edinburgh or elsewhere as well as self-funded students.
Funding Eligibility - Home applicants only (UK+EU settled/pre-settled)
Funding may be available for this project.
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In the context of long-term monitoring applications, there are numerous structural states that exhibit similar behavior but cannot be generalized with a single model (whether data- or physics-based) due to the inherent time-variant nature of structural evolution (1). Addressing such scenarios necessitates methodologies with adaptable models that can capture the interdependencies between Environmental and Operational Variabilities (EOV) and Damage Sensitivity Features (DSF) at various stages of structural evolution. The challenge lies in determining when distinct structures can be considered pseudo-similar, thereby sharing the same underlying physical properties to better represent the dynamics and associated EOV dependencies (2). Similarly, the incorporation of physics-based models, with varying levels of fidelity, adds knowledge towards understanding structural changes, which is essential for incorporating interpretable constraints on DSF evolution.
In practice, there are two main Challenges: (i) Robust extraction of DSF for continuous monitoring which are insensitive to EOVs. These DSF should be interpretable during the entire evolution of the structural performance and they should be able to accommodate dimensionality and complexity reduction of their associated non-linear time-variant nature. (ii) And there is a need of developing measures to quantify and propagate uncertainty towards the estimation of future stages of the structure evolution.
(1) Garcia Cava D., Avedaño Valencia L. D., Movsessian A., Roberts C. and Tcherniak D., On explicit and implicit procedures to mitigate environmental and operational variabilities in data-driven structural health monitoring. Chapter in the Book on Structural Health Monitoring Based on Data Science Techniques. Structural Integrity, Springer, pp. 309-330, vol 21, Cury A., Ribeiro D., Ubertini F., Todd M.D. (eds). 2021 (DOI: doi.org/10.1007/978 − 3 − 030 − 81716 −9 15)
(2) Qu, K., Logan, A., Miller, M. and Garc´ıa Cava D., Multi-phase adaptive methodology for mitigating environmental and operational variability in slowly changing time-variant engineering structures. Mechanical Systems and Signal Processing, 229:112494 , 2025. (DOI: doi.org/10.1016/j.ymssp.2025.112494)
Minimum entry qualification- an Honours degree at 2:1 or above (or international equivalent) in a relevant science or engineering discipline, possibly supported by an MSc Degree. Applications are particularly welcome from candidates expecting to receive a first-class degree in mechanical engineering, physics, applied mathematics or a closely related subject.
Further information on English language requirements for EU/Overseas applicants.
Applications are welcomed from self-funded students, or students who are applying for scholarships from the University of Edinburgh or elsewhere as well as sel-funded students.
*Competition (EPSRC) funding may be available for an exceptional candidate but please note you must be a UK student or an EU student who has lived in the UK 3+ years
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This project aims to investigate the capabilities of adaptive structures that change their geometry and mechanical properties to accommodate operational loading and damage management. The core objective of this project is to engineer an adaptive structure that adjusts to the prescribed loading conditions. This adaptation is achieved by integrating local structures that accommodate stiffness variations along the global structure.
The local structures will change their geometry and shape in response to the applied loads, resulting in emergent properties in the main global structure (1). Analytical modeling of the local-structures will provide understanding and control for stiffness tailoring, which will translate into desirable mechanical properties in the main structure. The connection between global properties and local-structure geometry changes aims to be achieved by understanding the relationships between geometric parameters and vibration response.
The geometric nonlinearity induced by the local-structures may cause amplitude-dependent nonlinear dynamic responses (2). Thus, understanding the underlying physics in the coupling between local and global structures, along with the vibration response of the global structure, aims to facilitate feedback to passively control the mechanical properties of the structure. Consequently, this dynamic response leads to continuous shape and geometry modifications within the structure, ultimately enhancing its capacity to accommodate specified loading requirements more effectively. The adaptive structures will benefit operability by maximising structural capacity during service. Interests on: Structural mechanics and dynamics, Stochastic modelling and Uncertainty quantification.
Website: https://dgarciacava.github.io/ Contact: David Garcia Cava (david.garcia@ed.ac.uk)
(1) Sundararaman, V., O’Donnell, M.P., Chenchiah, I.V., Clancy, G. and Weaver, P.M., 2023. Stiffness tailoring in sinusoidal lattice structures through passive topology morphing using contact connections. Materials & Design, 226, p.111649.
(2) Zhao, B., Thomsen, H.R., Pu, X., Fang, S., Lai, Z., Van Damme, B., Bergamini, A., Chatzi, E. and Colombi, A., 2024. A nonlinear damped metamaterial: Wideband attenuation with nonlinear bandgap and modal dissipation. Mechanical Systems and Signal Processing, 208, p.111079.
Minimum entry qualification- an Honours degree at 2:1 or above (or international equivalent) in a relevant science or engineering discipline, possibly supported by an MSc Degree. Applications are particularly welcome from candidates expecting to receive a first-class degree in mechanical engineering, physics, applied mathematics or a closely related subject.
Further information on English language requirements for EU/Overseas applicants.
Applications are welcomed from self-funded students, or students who are applying for scholarships from the University of Edinburgh or elsewhere as well as self-funded students. *Competition (EPSRC) funding may be available for an exceptional candidate but please note you must be a UK student or an EU student who has lived in the UK 3+ years
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We are offering a PhD opportunity focused on dynamical downscaling of regional ocean models. This studentship is supported as part of the EU-INTERCHANGE project, which aims to improve the accuracy and spatial resolution of regional ocean model data around Europe, having broad use cases in mind such as offshore energy and aquaculture. As global climate variability intensifies, precise regional modelling becomes crucial for developing effective mitigation and adaptation strategies for marine infrastructure.
Within the Institute of Infrastructure and Environment, we maintain a track record in the coupling, applications, and development of regional ocean models. Capitalising and contributing to this effort, this project will
- Investigate effective downscaling strategies for different regional ocean processes, exploring wave energy propagation and other marine hydrodynamics towards minimising uncertainty of low resolution datasets
- Participate in research aimed at the dynamical downscaling of ocean models using cutting-edge computational techniques, including machine learning algorithms.
- Work collaboratively with an interdisciplinary and international team to refine and validate regional wave and ocean forecasting models, stemming from use cases and data from a wide range of sites.
- Publish research findings in peer-reviewed journals and present results at both national and international scientific meetings.
- Collaborate with EU-Interchange project collaborators, including researchers from Delft University of Technology (TU Delft) and the Norwegian Meteorological Institute (MET Norway)
The PhD topic will be refined based on the selected candidate’s strengths and research interests, ensuring alignment with the broader objectives of the School of Engineering and the EU-Interchange project.
For further information and queries regarding this opportunities, reach out to Dr Athanasios Angeloudis (a.angeloudis@ed.ac.uk )
Minimum entry qualification -
- an Honours degree at 2:1 or above (or International equivalent) in Engineering, Oceanography, Computational Science, or a closely related field.
- Proficiency and interest in programming languages such as Python, MATLAB, or similar, used for large-scale data processing and model development.
- Excellent written and verbal communication skills, with the ability to engage effectively with diverse scientific communities.
- A proactive approach to problem-solving and an enthusiasm for collaborative research.
Further information on English language requirements for EU/Overseas applicants.
Tuition fees + stipend are available for applicants who qualify as Home applicants.
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Morphing is a ubiquitous feature in nature: from the growth of plants to embryos evolution to wing adaptation in birds, shape-change is a fundamental aspect of the biological matter itself. What makes this phenomenon compelling is not only its beauty in nature, but its potential to reshape the way we design novel artificial systems, like materials that can adapt to their environment or systems that respond dynamically to external forces. Such possibilities challenge conventional thinking in engineering and design. By studying how stresses, geometry, and material properties interact, we can develop systems that morph with intention rather than by chance. We are inspired by nature, that offers countless inspirations, but the challenge is to translate these elegant mechanisms into technical solutions.
Of particular interest are slender system where the mechanical response and the emerging shape is especially sensitive to the coupling between the mean of actuation and geometry.
The aim of the project is to develop new theoretical frameworks to understand the root causes of active morphing in two-dimensional membrane-like structures and to explore strategies for achieving desired shapes. A key aspect of the work is linking microscopic (discrete) mechanics to macroscopic (continuum) models of active slender systems.
The project involves three main components:
- Theoretical continuum modelling. Extend classical mechanics of two-dimensional bodies by incorporating active effects to study the competition between elasticity and controlled actuation in shaping slender objects.
- Theoretical discrete modelling. Establish quantitative connections between the continuum parameters and the underlying microscopic mechanics.
- Numerical study. Implement the models in computational codes to design and optimize morphing strategies.
During this project, you will be part of the Institute for Infrastructure and Environment. You will join a vibrant community of PhD students, postdoctoral research associates and academics.
Please note that the advert might close sooner, if a suitable candidate is found. Therefore, early applications are advised.
For informal enquiries please contact Dr Matteo Taffetani (matteo.taffetani@ed.ac.uk) and visit https://mtaffetani.github.io/
Minimum entry qualification - an Honours degree at 2:1 or above (or International equivalent) in a relevant science or engineering discipline, possibly supported by an MSc Degree. Further information on English language requirements for EU/Overseas applicants.
This project would potentially suit candidates from backgrounds in Structural and Mechanical Engineering, Engineering Mathematics, Applied Mathematics and Physics.
We are interested to hear from applicants with experience in mathematical modelling and who are keen to develop numerical codes (or improve numerical codes already available) to support the modelling conducted. The applicant should have an interest in applying their studies to experimental evidence gathered from literature or tabletop experiments. Although preferable, knowledge of mechanical concepts (like elasticity or equilibrium equations) is not essential. Familiarity with biological and active systems is not essential.
Tuition fees + stipend are available for Home/EU and International students.
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Surfaces in wet environments biofoul, which is a pressing issue affecting many industries, including water treatment industries: during membrane filtration, bacteria adhere on the membrane surface and biofouling forms, reducing water quantity and quality produced, increasing energy costs and requiring frequent harsh cleaning methods. Ultimately, cleaning becomes inefficient and irretrievable surface damage occurs, requiring complete replacement of the membranes. The objective of this project is to develop efficient cleaning strategies for membranes, including optimizing and testing innovative self-cleaning and anti-biofouling membrane polymeric coatings currently being developed by the team (https://www.sciencedirect.com/science/article/pii/S2352940725002719). The coating is light responsive, i.e. it will change its physical properties at the nano and microscale when subjected to visible light, allowing for surface biofouling to be removed with visible light, remotely and contactless. This translates to more sustainable cleaning practices by removing the need for chemical cleaning techniques with hazardous and toxic cleaning agents, or the need for harsh physical cleaning methods. Moreover, enhanced material reusability is achieved, translating to lower replacement needs and lowering operational costs. This project is part of the EPSRC Programme Grant “Decentralized Water Technologies” (https://www.offgridwater.org.uk/), a consortium of several Universities, aiming at accelerating the delivery of sustainable and low-cost decentralised water and wastewater technologies, by bringing most up-to-date bioscience and engineering together, so off-grid systems are configured with confidence.
Early application is advised as the position will be filled once a suitable candidate is identified.
This project is part of the EPSRC Programme Grant “Decentralized Water Technologies”: https://www.offgridwater.org.uk/
Minimum entry qualification - an Honours degree at 2:1 or above (or International equivalent) in a relevant science or engineering discipline, possibly supported by an MSc Degree. Further information on English language requirements for EU/Overseas applicants.
Further information and other funding options.
Tuition fees + stipend are available for applicants who qualify as Home applicants.
To qualify as a Home student, you must fulfil one of the following criteria:
- You are a UK applicant.
- You are an EU applicant with settled/pre-settled status who also has 3 years residency in the UK/EEA/Gibraltar/Switzerland immediately before the start of your programme.
Applications are also welcomed from those who have secured their own funding through scholarship or similar.
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Existing buildings entail a third of the energy consumption in the world and contribute a similar share of greenhouse gas emissions. At the same time, they have been shown to have a large potential for improvement in both fronts. Just enhancing operations of what is already in place is estimated to reduce energy and operational emissions by 20% on average.
A significant area of work has focused on whole-building analysis and simulation to rigorously understand performance of existing assets. Here, building audits are combined with holistic physics-based models to improve understanding of what is built and to devise ways to improve operations and retrofit packages. However, such an approach requires specialist knowledge and can easily become onerous given time, interrelationships of physical processes, and resources needed. In addition, it does not link well with metering and building management systems buildings have in place as they only monitor buildings partially.
This project seeks to investigate the role of progressive energy modelling to assist facility managers understand and improve the performance of existing assets. Building systems can be modelled in a wide range of ways, and it is possible to isolate components for dedicated analyses. Then, they can be extended to include further parts relevant to the system. As an example in HVAC systems, heating/cooling generation via heat pumps or boilers could be analysed with a dedicated model, aided by monitoring points typically implemented, like supply/return temperatures or partial loads. Once it is verified that the system works as expected, the model can be extended to represent further parts of the whole system, like losses in distribution systems, emitters, or links with ventilation systems.
Compared to whole-building simulation, this is a bottom-up modelling approach that conceives buildings as a jigsaw of systems that have a closer correspondence with established monitoring practices in facility management. It simplifies complexity, offers faster feedback cycles, retains meaning to explore alternative ways of operating buildings, and could be done in a way that paves the way to whole-building modelling as required.
We are seeking applicants wishing to advance the state of the art in this area, including exploring the role of model complexity, model interoperability, and influence on facility managers' decision-making processes.
This is a joint PhD project between The University of Edinburgh (Dr Daniel Fosas) and Heriot-Watt University (Professor David Jenkins). The context of the work will be the campuses of these institutions and students will have access to their combined training opportunities. We welcome applications from all qualified candidates, and we wish to particularly encourage applications from groups underrepresented at this level.
To apply to this opportunity, you will need to:
We are available to discuss and give feedback to applicants that meet entry requirements. A comprehensive training programme will be provided comprising both specialist scientific training and generic transferable and professional skills. The PhD candidate will be introduced to comprehensive training options, within The University of Edinburgh and Heriot-Watt University. The candidate will have the opportunity to become a teaching assistant following formal training, as well as opportunities to contribute to wider training and outreach activities. Further training in both academic and interdisciplinary skills will be available as part of Edinburgh’s Institute for Academic Development. |
Minimum entry qualification - an Honours degree at 2:1 or above (or International equivalent) in a relevant science or engineering discipline, possibly supported by an MSc Degree.
A background related to building performance simulation and building services engineering would be an advantage for the project. The project will require development of building simulation models, off-the-shelve and bespoke ones, and data mining: familiarity or willingness to learn programming languages like Python, Julia, or R will be essential
Please click on this link for further information on English language requirements for EU/Overseas applicants.
Applications are welcomed from self-funded students, or students who are applying for scholarships from the University of Edinburgh or elsewhere.
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