Multiscale Thermofluids

Are you eager to push the frontiers of fluid dynamics and AI to tackle real-world challenges in crowd safety, urban planning, and event management? Join our EPSRC-funded project FLOCKS (Fluid dynamics-Like Open-source Crowd Knowledge-driven Simulator) as a PhD student and help shape the future of crowd modelling.

FLOCKS aims to develop the world's first real-time, open-source simulator of large, dense crowd dynamics for both academic and industrial applications. 

Your research will focus on creating a continuum-based fluid dynamics model of human crowds, treating them as "thinking fluids" and using coarse-grained observables, such as density, mean velocity, and stress-like quantities, as descriptors. Drawing on active matter modelling, you will explore ways of incorporating the non-local perception and decision-making of pedestrians into constitutive relationships and boundary conditions with the aim of capturing realistic crowd behaviour. Where possible, you will also explore coupling the crowd model with hazards such as the spread of smoke and fire during incidents, contagion in pandemics, or violence in demonstrations, which will enable a multi-risk approach to assessment and decision support in high-stakes scenarios. 

You will work closely with a postdoctoral researcher to develop complementary data-driven approaches that use machine learning to inform, parameterise and validate crowd dynamics models. This collaboration will establish a continuous feedback loop to refine your model and provide valuable opportunities for knowledge exchange.

You will implement the final model in an open-source simulation environment, and your final demonstrator will simulate iconic Edinburgh events (e.g. Hogmanay on Princes Street, an Edinburgh derby football match, or a Murrayfield Stadium concert) using pre-captured datasets to showcase the predictive capabilities of the simulator.

Thanks to our partnerships with world-leading experts in crowd safety engineering and open-source software development, your work will directly impact public safety, urban planning and event management in the real world.

It is intended that the PhD start date will be 1 March 2026, and applicants should select that entry point when applying to the PhD programme.

Minimum entry qualification

• First or Upper Second-Class (2:1) honours degree or equivalent in Engineering, Physics, Applied Mathematics or a clearly related area, with a focus on continuum mechanics, differential equations, and numerical methods or a closely related area.
• Evidence of research in computational engineering, with a specific focus on hydrodynamic modelling of complex systems or a closely related area.
• Proficiency in scientific programming (e.g., Python, Fortran, C++).

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

Desirable criteria

• Training in machine learning, ideally applied to model discovery and physics-informed approaches.
• Experience of computational fluid dynamics or agent-based simulation software.

Further information and other funding options.

School of Engineering stipend for 3.5 years, home or overseas fees, £5k research costs (over the duration of the project). The stipend rate for academic year 2025/26 is £21,935. 

Whether it is the substantial cooling requirements of future data centres or energy-dense batteries for next-generation electric vehicles, the need for energy-efficient electronics cooling systems is ubiquitous. This is because while recent developments have produced ever-smaller and ever-denser devices, heat fluxes comparable to the surface of the Sun can be generated at hot spots, producing high temperatures that adversely impact their performance and raise risk of catastrophic failure. In the last decade and a half, novel 2D nanomaterials have been developed with unique thermal properties (e.g. ultrahigh thermal conductivity). These nanomaterials can be used to form surface coatings to enhance heat transfer from the extremely hot surfaces of electronic devices into the adjacent coolant liquid. 

However, our understanding of thermal transport at this nanomaterial/liquid interface is currently limited. For 2D nanocoatings, the nanomaterial can be either carbon-based (graphene nanoparticles or nanoflakes, nanopores, graphene oxide nanosheets etc), boron-based (boron nitride nanosheets, nanotubes, etc) or hybrid (e.g. boron carbon nitride). Similarly, while water is the most studied coolant liquid, realistic applications involve dielectric fluids (e.g. benzene, pentane). Molecular dynamics (MD) simulations represent a powerful tool to study such interfaces, but MD of nanomaterial/liquid interfaces require well-calibrated intermolecular potentials, which don’t currently exist. This project will rely on recent advances in neural networks to develop machine learning potentials (MLPs) for MD simulations of realistic nanomaterial/coolant-liquids and use these to gain fundamental insights into interfacial thermal transport. The goals are to:

1) run ab-initio molecular simulations to sample relevant nanomaterial/liquid interfaces.

2) construct new MLPs by using generated data from 1) and validate them.

3) use MLPs to run classical MD simulations and characterise thermal transport.

This PhD project will be based within the School of Engineering, University of Edinburgh. This PhD project will be supervised by Dr Rohit Pillai and Dr Eleonora Ricci, and the successful applicant will join an active, friendly, and collaborative research group (see https://multiscaleflowx.github.io/). Our group makes extensive use of ARCHER2 – the UK’s national supercomputer, which is based in Edinburgh. This PhD will give the successful applicant the skills and experience to become a future leader in either academia or industry. The supervisors will provide the successful applicant with exceptional research and training opportunities, including:

• regular weekly meetings to discuss the research progress.

• opportunities for travel to participate in workshops/summer schools dedicated to advanced computational methods, as well as present results in international conferences.

• training and experience in state-of-the-art engineering research.

• mentoring from other investigators and experienced postdoctoral researchers.

• exceptional career development opportunities with strong institutional support of early career researchers.

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.

The Place - Edinburgh Research Partnership in Engineering (ERPE)

ERPE is a strategic alliance between Heriot-Watt University (HWU) and the University of Edinburgh, UoE, as two of the UK's leading research universities in STEM. ERPE works with academics, industry and public sector partners to deliver world-leading engineering solutions and create commercial, social, environmental and economic impact. This PhD project involves a collaboration between the Institute for Multiscale Thermofluids (IMT) at the School of Engineering of UoE, and the School of Engineering and Physical Sciences (EPS) at HWU. IMT is recognised in theoretical and experimental characterization of interfacial and reactive multiphase flows, while EPS combines a longstanding reputation in the energy sector and a pioneering role in the UK industrial decarbonisation with the new Global Research Institute GRI iNetZ+. The successful candidate will be co-supervised by Dr Khushboo Pandey from UoE and Dr Victor Francia from HWU. They will join Experimental MultiPhysics and MultiPhase flow group, E(MP)2 Group at UoE, and xFlow (Complex Flow Technologies) at HWU. The E(MP)2 Group at UoE focuses on experimental investigation and theoretical modelling of complex muliphase systems, specifically, particle dynamics and spray characteristics in extreme and turbulent conditions for developing sustainable energy technologies for power and propulsion. xFlow focuses on technology development, looking at new platforms with potential to disrupt the energy and manufacturing sectors. They intensify gas-solid operations and integrate them in the design of new circular processes to allow traditional chemical and biochemical industries to adopt sustainable practices quickly and efficiently.  

The Project

In this project, we will work towards a fundamental understanding of complex particle dynamics in near-wall flow structures, such as deposition, resuspension and agglomeration. Deposition and resuspension are critical phenomena across a broad range of disciplines. Transport, deposition and resuspension of particulate matter and solid aerosols is ubiquitous in nature, and it has a direct impact in sectors spanning heath care (transmission of disease vectors) to renewable energy and space exploration (efficiency of solar panels), and a very broad range of manufacturing and environmental technology, from deposition on traditional multiphase reactors to water remediation technology, and the manufacturing of advanced materials via spray drying, granulation, coating, electrospraying. This project will advance the fundamental understanding of particle-particle interactions in wall-bounded flows, how particle flow, interact, deposit, agglomerate and resuspend in shear and swirling turbulent boundary small-scale wind tunnel and vortex flow chambers at the Small Research Facility for Multi-phase Flows at High Pressure and Temperature (UoE) and within REVOC (EPSRC-funded project k768£ FE) at xFlow laboratories (HWU). The PhD candidate will employ state-of-the-art flow visualization diagnostics (high-speed shadowgraphy, Particle Image Velocimetry, among others) to understand the particle dynamics in wall-near regions and quantify transport properties, flow structures and rate of deposition, resuspension and agglomeration ideal particulate systems. The fundamental dynamics studied here will find application in the validation of high-fidelity models of particle flow and the development of digital twins for a broad range of processes, from healthcare to energy and sustainable manufacturing.

Interested candidates are advised to contact Dr Khushboo Pandey kpandey@ed.ac.uk from UoE and Dr Victor Francia, v.francia@hw.ac.uk from HWU. 

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

The selected candidate will be invited to apply to a PhD position via the University of Edinburgh website and will be put forward to a competitive selection process by ERPE, the Edinburgh Research Partnership in Engineering.

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.

The ideal candidate would have a Master Level degree in mechanical / chemical engineering / physics or a related discipline with outstanding record. The candidate would have a strong interest in experimental multiphase flow and flow visualisation. The candidate would also need to be fluent in English, be proactive, independent and with a can-do mentality.  

Applications to be received by 7 / 02 / 2025. The expected start date is September 2025 after the completion of a competitive selection process within ERPE. Scholarships are open to UK applicants or exceptional oversea applications. Interested candidates are advised to contact Dr Khushboo Pandey kpandey@ed.ac.uk from UoE and Dr Victor Francia, v.francia@hw.ac.uk from HWU.  

• A CV  
• BEng/Meng/MSc grades  
• A motivation letter explaining your interest/aptitudes for this position

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.

Nucleate boiling is a type of boiling mechanism where the heat is transferred from a hot surface to a liquid through the formation and release of vapor bubbles. This process occurs at discrete points on the surface where the liquid is in direct contact with heat. During nucleate boiling, small bubbles of vapor form at nucleation sites, typically surface imperfections, and grow until they are buoyant enough to detach and rise through the liquid. Surface modification is a passive method to increase heat transfer in nucleate boiling by controlling bubble nucleation and detachment using structures or coatings that modify a surfaces morphological parameters.

Recently, we developed new techniques to modify surfaces with regions that could act as nucleation sites and provide easy bubble detachment. These patterned liquid-like surfaces are based on Slippery Covalently Attached Liquid-like Surfaces (SCALS). In this experimental project, you will tackle questions involving nucleate boiling on patterned liquid-like surfaces:  we are interested in understanding how these surfaces act under boiling conditions and their effects on the efficiency of heat transfer and maintaining a stable heat flux. By answering questions like these, you will be pushing the boundaries of knowledge in this field and kick-start your postgraduate career.

If successful, you will become a member of the Wetting, Interfacial Sciences and Engineering Group within the Institute for Multiscale Thermofluids at the School of Engineering. You will join a vibrant community of PhD students, postdoctoral research associates and academics working in various aspects of surfaces and wetting, and will develop as a scientist benefiting from our track record, which includes publications in top journals, international collaborations and contributions to key international conferences.

Please note that the supervision team will include:

Principal supervisor

Dr Gary Wells: https://www.eng.ed.ac.uk/about/people/dr-gary-wells

Assistant supervisors

Professor Glen McHale: https://www.eng.ed.ac.uk/about/people/professor-glen-mchale

Dr Rodrigo Ledesma Aguilar: https://www.eng.ed.ac.uk/about/people/dr-rodrigo-ledesma-aguilar

Please note that if a suitable candidate is found prior to the closing date, then the position will be closed and the advert will be removed.

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.

We expect that you will have a good degree in Engineering or Physics with an experimental and modelling background. We are particularly interested to hear from applicants with experience in surfaces, fluids and/or phase change.

Please note that if a suitable candidate is found prior to the closing date, then the position will be closed and the advert will be removed.

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.

If we stretch a material, such as a rubber band, in one direction we observe it contracts in the lateral direction. However, a material can be designed to be counterintuitive so that when it is stretched in one direction it also expands in the lateral direction. A material with this unusual property is called a mechanical metamaterial (an auxetic material). The pore sizes in such materials can therefore be changed by strain. A mechanical metamaterial with a hydrophobic surface can be converted by strain to a super-water-repellent material or to a porous material.

In this project, the focus will be on creating hydrophobic mechanical metamaterials using foams and characterizing their properties when in contact with different liquids. The project will also consider a possible application in the programmable separation of oil-water mixtures and de-fouling of materials. The project will investigate whether strain might be used as a switch to allow oil to either be blocked to to pass through the material and whether strain can be used to release particulates blocking the material when it is used as a filter.

The PhD researcher will be part of the Wetting, Interfacial Sciences and Engineering Group within the Institute for Multiscale Thermofliuds. You will join a vibrant community of PhD students, postdoctoral research associates and academics working in various aspects of surfaces and wetting. The student will attain skills in materials preparation, surface coating, construction of experimental set-ups, and measurement techniques and characterization techniques.

It is expected that the applicant will have a good degree in chemical engineering, mechanical engineering, materials science, physics, or a related discipline.

Please note that if a suitable candidate is found prior to the closing date, then the position will be closed and the advert will be removed.

For further information on this project, please refer to the following website: http://www.naturesraincoats.com/

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.

Further information and other funding options.