Infrastructure and Environment

Context

Reverse osmosis (RO) holds significant promise in alleviating global water scarcity through seawater desalination. But shortages of increasing frequency and intensity now demand treatment of unconventional waters beyond seawater, such as wastewater, to expand supply. RO is also increasingly deployed to treat industrial streams in microelectronics, pharmaceutical, and food & drink manufacturing, which must meet stringent water quality standards. In all cases, RO polyamide (PA) membranes – originally designed to reject charged (ionic) species in seawater – are increasingly challenged by small charge-neutral contaminants (SNC) that pass through largely unrejected. SNC include toxic disinfection by-products (e.g., nitrosamines) and organic pollutants (trihalomethanes, phenols, dioxanes, alcohols, ketones); their removal requires additional energy-intensive treatment stages. 

Answering the following two long-unresolved research questions (RQ) is key to shifting from a trial-and-error approach to rational membrane design, and achieving transformative improvements in SNC rejection: RQ1. What are the molecular-level mechanisms governing sorption and transport in RO membranes? RQ2. How can insights into sorption and transport be leveraged to efficiently search a vast library of possible membrane materials – the chemical design space – and discover highly selective, water-permeable membranes?

Objectives

We will tackle RQ1-2 through simulation and experiment to achieve our Overall Objective: to computationally discover new membrane materials for SNC removal by harnessing molecular dynamics (MD) simulation and machine learning (ML).

The project is structured along the following two Works Streams (WS) addressing RQ1-2. In WS1, MD simulation will elucidate molecular-level sorption and transport mechanisms, providing insights into the optimal membrane properties – pore sizes, interfacial chemistry – that boost selectivity. In WS2, a vast chemical design space formulated with insights from WS1 will be explored using a ML technique enabling computationally-efficient materials discovery. 

Research and Training

The successful applicant will conduct research in the School of Engineering at the University of Edinburgh, under the supervision of Dr Santiago Romero-Vargas Castrillón. The student will have access to a wide range of computational facilities. Educational and research opportunities afforded by this project include: 

• training in state-of-the-art molecular simulation techniques 

• close mentoring through regular meetings, as well as interactions with other investigators at the Institute of Multiscale Thermofluids (IMT) and the Institute for Infrastructure and Environment (IIE) at Edinburgh 

• the opportunity to attend national and international scientific conferences to disseminate your results 

• strong emphasis and support to publish research results in leading scientific journals, which will kickstart your career in academia or industry. 

This is a challenging and scientifically ambitious project, requiring a student who is dedicated and enthusiastic about asking, and tackling, fundamental questions. The successful applicant will have been awarded an undergraduate degree at the time of appointment (2:1 or above, preferably supported by an MSc) in chemical engineering, mechanical engineering, chemistry, physics, materials science, or a cognate field. A strong background in mathematics and physics is required, as well as interest in molecular simulation. Prior research experience in modelling and simulation is highly desirable.

We accept applications from qualified self-funded students. Qualified UK applicants (or those with EU settled status) may be supported to apply for highly competitive School of Engineering studentships.

Further information and other funding options.

Global context: By 2050 the global population is projected to reach nearly 10 billion, requiring an estimated 56% increase in food production compared to 2010, on less land, with fewer resources, and under mounting climate pressure. Crop protection products are essential to this challenge, safeguarding harvests from pests, weeds and disease. But manufacturing these agrochemicals sustainably is one of the industry's hardest unsolved problems. 

Scientific challenge: At the core of agrochemical manufacture lies filtration: separating solid crystalline product from the surrounding liquid. Many of these crystals grow as tiny rods, and their elongated shapes make them notoriously difficult to separate efficiently. Poor filtration means wasted product, wasted energy, and wasted water. Getting it right, can unlock cleaner, cheaper, more sustainable production at scale. 

This project: You will build particle-based physics simulations of rod-shaped crystals as they pack, flow and form filter cakes. Using fundamental physics, contact mechanics and hydrodynamics, you'll reveal exactly how rod geometry, orientation and packing govern filtration performance. From these insights, you'll help optimise the process itself, turning trial-and-error into predictive design. 

Why it matters: Your work will directly target UN Sustainable Development Goal 2: Zero Hunger, while cutting the energy and water footprint of manufacturing. You'll contribute to making a vital global industry genuinely sustainable. 

What you'll gain: 

• Expertise in computational modelling, soft-matter physics and particle simulation. 

• Expertise in written and verbal communication. 

• Real-world industrial relevance and collaboration. 

• Skills spanning coding, physics and chemical engineering, which are highly sought after in academia and industry.

We're looking for: A curious, motivated graduate in physics, chemical engineering, applied maths or a related field, with an appetite for problem solving.

Dixon, A., Hone, J., Melaugh, G. and Ness, C., 2026. Rheology of dense suspensions of granular spherocylinders by particle-based simulation. arXiv preprint arXiv:2607.28206. Ness, C., Seto, R. and Mari, R., 2022. The physics of dense suspensions. Annual Review of Condensed Matter Physics, 13(1), pp.97-117.

A UK 2:1 honours degree, or its international equivalent, in an appropriate subject, or relevant qualifications and experience.

There may be industry funding available for this project for Home applicants (UK & EU with settled/pre-settled status), please enquire.

Applications are welcomed from self-funded students, or students who are applying for scholarships form the University of Edinburgh or elsewhere.

Further information and other funding options.

Flame spread over solids is a key aspect of fire science. It shapes how we assess the hazard of materials and systems, from the built environment to wildland fuels. Yet our ability to predict flame spread rates remains limited, even after decades of research. The main reason is that the governing processes occur in a narrow region near the leading edge of the flame, where heat transfer, gas-phase chemistry, and fluid mechanics are strongly coupled and where the measurements needed to separate and quantify these effects have been largely unavailable. 

The project will address the current knowledge gaps by building a new experimental picture of flame spread. The aim is to generate the measurements required to (i) improve fundamental understanding and (ii) provide a high-quality dataset for the development and validation of predictive numerical models. You will study opposed flame spread (OFS) and concurrent flame spread (CFS), with an emphasis on the interactions between the environmental variables and the resulting flame spread rate and the controlling processes. A central theme is to quantify what sets the flame spread rate by closing the energy balance near the spread front and linking it to the flame structure and mixing/chemistry length scales. The work will use and integrate a range of experimental methodologies and will specifically seek to bridge the gap between fire science methods and more advanced optical diagnostics which may include high-resolution gas-phase thermometry and species measurements, surface temperature diagnostics for pyrolysing solids, flow-field measurements to resolve mixing, and diagnostics relevant to soot/radiation. 

This PhD project is aligned with the EPSRC-funded project Shining a Light on Flame Spread and the successful candidate will join a team composing a postdoctoral research associate, experimental officers and an existing PhD student, as well as the academics.

https://eng.ed.ac.uk/fsmm 

Candidate profile:

We are looking for a candidate with a strong background in Chemical Engineering, Mechanical Engineering, Applied Physics, or a closely related area. You should be comfortable with quantitative thinking and keen to work at the interface of experiment and analysis. 

Useful experience (not essential) includes: 

• heat transfer, fluid mechanics, combustion, transport phenomena, or thermodynamics 

• experimental work in fire science or experience with optical diagnostics 

• data analysis and programming (e.g., Python/Matlab) 

• careful experimental practice, uncertainty awareness, and clear communication 

This PhD suits someone who wants to develop high-level experimental skills and produce results that directly support the wider fire science and modelling community, with relevance to fire safety challenges in the built and natural environments.

Funding is available to Home applicants (UK & EU with settled/pre-settled status).

Further information and other funding options.

Why join this project? 

This PhD project is part of HORUS 4D, a £2.2M consortium comprising six academic institutions in the UK and France dedicated to advancing 4D printing. The selected candidate will operate at the forefront of morphing structures research, developing foundational principles that could support future technologies across aerospace, space systems, robotics, transportation, and biomedical devices. They will have access to cutting-edge manufacturing and characterisation facilities and will be immersed in a research environment focused on high-impact, interdisciplinary engineering science. The position offers numerous networking opportunities, including participation in workshops and international conferences. Additionally, three-month secondments at partner institutions will be incorporated into the work plan. 

Host: School of Engineering, The University of Edinburgh, UK, ESTACA Ecole d’Ingénieurs, France. Supervisors: Francisca Martinez Hergueta, Matteo Taffetani, Thuy-Quynh Truong-Hoang, Marcelo Dias 

Funding for eligible candidates is sponsored by Dstl. 

Successful candidate will be expected to start their position in September 2026 (duration 3 years).

How to apply 

Please submit: 

1. CV (including relevant projects and technical skills) 

2. Cover letter / personal statement (max 300 words) explaining your interest in 4D printing/morphing structures and how your skills match the project 

3. Academic transcripts (or list of grades if transcripts are not yet available) 

4. Names/contact details of two referees

Minimum criteria: 

• a 2:1 undergraduate degree (or equivalent).
• the University’s English language requirements.

Tuition fees + stipend are available for Home students only

To qualify as a Home student, you must fulfil one of the following criteria:

- You are a UK student

- You are an EU student with settled/pre-settled status who also has 3 years residency in the UK/EEA/Gibraltar/Switzerland immediately before the start of your Programme. (International students not eligible.)

Further information and other funding options.