Multiscale Thermofluids

We invite applications for a PhD position to advance flue gas cleaning technologies from industrial emissions, particularly in Energy-from-Waste (EfW) power plants. The EfW solutions incorporate advanced flue gas cleaning systems that notably reduce landfill waste, lower emissions, generate energy, and assist in material recovery, thus supporting a sustainable closed-loop circular economy. The appointed researcher will contribute to the EPSRC funded M2CLEAN project, which intends to thoroughly investigate the complex dynamics of particle interactions at various scales, including those between solid particles, liquid droplets, and gas phases. The research work will tackle key operational challenges such as regulating temperature and humidity, alongside optimising particle size and distribution to increase emission removal efficiency. The primary goal of this project is to create experimentally informed predictive models that detail these inter-particle interactions, enhancing understanding and efficiency of semi-dry flue gas cleaning systems.

The current Ph.D. position focuses on the experimental investigation of particle-droplet interactions under acoustic levitation. The project aims to foster a new understanding of the spatiotemporal scales and the controlling parameters of particles when subjected to varying temperature and humidity. The project offers hands-on experience in setting up multiphase experiments and using several state-of-the-art optical diagnostics, such as high-speed shadowgraphy, Particle Image Velocimetry (PIV), and Planar-Induced Fluorescence (PLIF).

The ideal candidate will be interested in fluid dynamics, reacting flows, and laser diagnostics and have programming experience in at least one language (e.g., Python, MATLAB, etc.). The selection process considers the comprehensive strength of the entire application, including the academic qualifications, personal statement, CV, and references. Ideally, candidates should have a strong background in fluid dynamics and the development of experimental methodologies.

The project includes close collaboration with TU Darmstadt, Germany and industrial partner Kanadevia INOVA, Zurich, Switzerland. This collaborative environment will offer the opportunity to learn from and contribute to a diverse team of experts. 

The intended PhD start date is in beginning of April 2026. If a suitable candidate is found, this position may close earlier than the closing date. 

Informal inquiries may be addressed to Dr Khushboo Pandey at kpandey@ed.ac.uk.

Minimum entry qualification - an Honours degree at 2:1 or above (or International equivalent) in a relevant science or engineering discipline. The candidate should have a master’s degree in either Physics or Engineering.

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

Tuition Fees and stipend are avilable for Home/EU and International students.

Further information and other funding options.

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.