Infrastructure and Environment

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:

1. 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.
2. Theoretical discrete modelling. Establish quantitative connections between the continuum parameters and the underlying microscopic mechanics.
3. 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. 

Further information and other funding options.

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.

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.

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.

Further information and other funding options.

A 3.5-year fully funded PhD studentship is available at the School of Engineering, The University of Edinburgh, in the field of Transport Engineering and Planning. This is an open call for highly motivated candidates eager to contribute to cutting-edge research in transport systems, mobility, and infrastructure.

Potential areas of study include (but are not limited to):

• Big Data and AI in Transport
• Traffic Operations, Modeling, and Simulation
• Infrastructure Resilience and Adaptation
• Urban Mobility and Multimodal Transport
• Equitable and Inclusive Transport Planning

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 supervisor’s expertise.

Minimum entry qualification: an Honours undergraduate degree at 2:1 or above (or International equivalent) in Transport Engineering or Planning, Civil Engineering, Mechanical Engineering, Computer Science, or a related discipline. 

- a Master’s degree is preferred but not mandatory. 

- programming experience (Python, R, C++, or similar) is desirable but not essential.

Further information on English language requirements for EU/Overseas applicants.

Tuition fees + stipend are available for Home/EU and International students

Further information and other funding options.

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 devise ways to improve operations and devise 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 for applicants wishing to advance the state of the art in this area, exploring model complexity, model interoperability and influence and acceptability for facility management and decision making.

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.

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.

This project is competing for one of the twelve studentships ring-fenced for the strategic partnership in Engineering between the University of Edinburgh and Heriot-Watt. Awards will be made on a competitive basis and there will be a first sift panel by the prospective supervisory team, and a second sift panel at school-level. Funding is offered for 3.5 years with an enhanced stipend of £21,400 (10% above the standard UKRI rate) and fees as well as £5,000 for support budget for the whole programme.

Further information and other funding options.

Asphalt recycling gained prominence since the 1970s, partly initiated by the oil crisis influencing the availability of bitumen as binder material. Since then, recycled and reclaimed asphalt continued to be part of the mix used in road and pavements providing a cost effective and environmentally friendly option with a potential to decarbonising the industry. Recent examples of roads using recycled asphalt include: 50% recycled asphalt was used in paving a section of M25 between junctions 25 and 26 and a section of A388 Bournemouth Spur Road, Dorset was paved using all the old road materials.  

Rolled asphalt pavement comprises of different courses primarily the wearing, binder, base, subbase and capping layer. The degree of compaction determines the stiffness and strength of material along with its resistance to deformation and durability of the mixture. Compaction of the asphalt along with the binder results from the operation of the paving/construction equipment to impart systematic static, shearing and vibrational loads to achieve the required properties of each of the aforementioned course. The pavement is expected to withstand the design traffic load.  

In the drive towards net zero carbon emission, there is an urgent need to significantly increase the use of the 100% recyclable Recycled Asphalt Pavement (RAP) in pavement construction.  This poses significant challenges in the design and optimisation of the production and construction processes for which this current project seeks to address. For instance, is it possible to better characterise the RAP in terms of material properties to provide a more accurate initial assessment of its recycling readiness? Is it possible to match to assess, based on the RAP's material characteristics and the prevailing loading regimes, whether it would meet the required highway standards?  

The aim of the project is to develop a deeper understanding of the RAP pavement construction and establish an experimentally calibrated numerical model to predict the compaction mechanics of recycled asphalt pavements during construction as well as operational period. The model will integrate the mechanics at different length scales. Experimental programme will include time-resolved (4D) X-ray tomography to capture the micromechanics of the granular assembly.  

This PhD project is advertised as a part of the Edinburgh Research Partnership in Engineering, a joint partnership between the University of Edinburgh and Heriot-Watt University. The successful candidate will be supervised by a team consisting of academics from the University of Edinburgh and Heriot Watt University (HWU). The Heriot-Watt University supervisor for this project will be Dr Elma Charalampidou. Some of the experiments involving micro x-ray CT system will be undertaken at HWU.

The selection process is in two phases:

Stage 1: Interested candidates should contact Dr Amer Syed at Amer.Syed@ed.ac.uk by 7 February 2025 with their CV and a covering email. Potential candidates will be invited to an interview. Selected candidate will progress to Stage 2.

Stage 2: Selected candidate will complete a formal application to the University of Edinburgh by 12 February 2025. This application will be assessed by a panel for funding. Please note that this studentship attracts enhanced stipend, while the exact details yet to be finalised, for 2024, it was £21,400 per annum.

Home and overseas students are encouraged to apply. 

The University of Edinburgh is committed to equality of opportunity for all its staff and students, and promotes a culture of inclusivity. Please see details here: https://www.ed.ac.uk/equality-diversity 

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.

Tuition fees + stipend are available for Home/EU and International students.

Further information and other funding options.