Dynamics of Liquid Droplets at Micro Scales

Key information

Lead supervisor: Dr J Rafael Castrejon-Pita
Application deadline: 11 May 2026
Project start date: 01 October 2026, or soon after
Project duration: 4 years (full-time)
Location: UCL East Campus (Stratford, London)
Studentship funding provided: Home tuition fees (currently £6,400/year) and maintenance stipend (currently £23,805/year) for 3.5 years

PhD project description

A fully funded 3.5-year PhD studentship is available under the supervision of J Rafael Castrejon-Pita within the Manufacturing Futures Laboratory in the Department of Mechanical Engineering, University College London.  

The project is focused on the dynamics of Liquid Droplets at micro scales. The project will use techniques such as High-Speed Imaging, Image Analysis, and Machine Learning to characterise and fluid and flow properties. The project will see major collaborations with UK inkjet industrial partners.

Background

It is generally accepted that numerous aspects in the field of liquid droplets remain to be understood. Endless natural processes depend on the formation of droplets, and even though they have been scientifically studied for more than 200 years, some fundamental principles behind droplet formation and impact dynamics remain elusive. 

The simple process of droplet breakup, jetting and impact onto a solid surface, gives rise to a plethora of mathematical complexities. For example, during dripping, a droplet must break away from the liquid that remains at the nozzle, then travel through air to eventually impact, and potentially splash onto a substrate or a liquid pool. Part of the problem is the multi-variable and multi-scale nature of these processes; past work has determined that the dynamics depends on a variety of factors, such as the substrate wettability, roughness, heterogeneities, the liquid properties at the relevant time scales, aerodynamic effects, and other flow characteristics. 

This PhD project aims to study the effect of these variables on the jetting, landing, and spreading of droplets. The approach combines experimental and theory-driven methodologies. 

Aim

This project will enable breakthroughs in the understanding of the intricate dynamics of liquid droplets by developing innovative experimental methodologies, and other approaches inclusive of machine learning. The aim is to further study the effect of liquid properties on droplet jetting, landing and spreading dynamics. As part of the project, we will visualise droplet behaviour over a large range of conditions including those found in nature and industrial environments. Our experiments will include droplet sizes from the micrometre to millimetre scales, our studies will cover colloidal, elastic, viscoelastic and other liquids. 

The candidate is expected to work jointly with academic and industrial collaborators from relevant areas such as inkjet printing and microfluidics. During this project, the candidate will conduct the research employing a range of advanced experimental, prototyping and data-driven approaches.

The position also offers opportunities to engage in teaching assistant activities within our department. As a PhD student at UCL, the candidate will benefit from training in high-impact research. The candidate will be encouraged to publish work in leading journals and present findings at national/international conferences.

Person specification

This PhD project would suit a highly motivated student possessing a mix of experimental and computational abilities. Good knowledge of fluid mechanics is expected and knowledge of Machine Learning is a plus. Experience in programming (e.g. Python, Matlab) would also be beneficial.

• Applicants are preferred to have, or be about to receive, first-class undergraduate and master’s degrees (or equivalent) in Mechanical Engineering or a related discipline with interest in fluid mechanics, experimental science, machine learning, and data analysis.
• Excellent organizational, interpersonal and communication skills, along with a stated interest in interdisciplinary research, are essential.
• Experience in computer programming and strong knowledge data driven methods is desirable.
• The project will suit a student with interest/background in fluid mechanics and experimental techniques. Practical experience of creating mechanical drawings, prototyping, electronics, and 3D printing will be beneficial. Neither need nor want constant supervision; independency is critical.
• Fluency and clarity in spoken English as well as good written English in accordance with UCL English requirements (TOEFL>92 or IELTS>6.5).

Eligibility

Please note that the available funding supports tuition fees at the Home/UK rate. Students who are eligible to pay fees at the UK rate are welcome to apply. Please refer to our website for further information about Home tuition fee eligibility.

International students who are eligible to pay tuition fees at the Overseas rate are also welcome to apply, however the tuition fees covered by the studentship will be limited to the Home/UK level. International students will be required to find additional funding for the remaining Overseas tuition fees.

Applicants whose first language is not English are required to meet UCL’s English language entry requirements.

Please refer to this webpage for full eligibility criteria: Mechanical Engineering MPhil/PhD

How to apply

Eligible applicants should first contact Dr J Rafael Castrejon-Pita (r.pita@ucl.ac.uk). Please enclose the following documents:

• A personal statement (500 words maximum) outlining (i) your suitability for the project with reference to the criteria in the person specification, (ii) what you hope to achieve from the PhD and (iii) your research experience to-date.
• A CV, including full details of all University course grades to date, and, if relevant, details on scholarships, prizes and scientific papers published or in preparation.
• Academic transcripts for undergraduate (Bachelor) and graduate (Master) studies.
• Names, and email addresses of two academic or professional referees (at least one academic).
   

After discussing the project with Dr Castrejon-Pita, eligible applicants should also submit a formal PhD application via the UCL website.

The supervisory team will arrange interviews for short-listed candidates.