University of Southampton
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PhD in Scientific Machine Learning for Fluid Dynamics and Hydraulics University of Southampton in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Competition funded PhD project. Funding opportunities are available for UK and international students. Horizon Europe fee waivers may cover the difference between overseas and UK fees for qualifying students. Competition-based Presidential Bursaries may cover the fee difference for top-ranked applicants. Competition-based studentships may cover UK-level tuition fees plus a living stipend for top-ranked applicants. Funding is awarded on a rolling basis.
Deadline
May 1, 2027
Country
United Kingdom
University
University of Southampton

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About this position
PhD opportunity at the University of Southampton in Scientific Machine Learning for Fluid Dynamics and Hydraulics.
This project focuses on Physics-Informed Neural Networks (PINNs) and their use as efficient alternatives to traditional computational fluid dynamics methods. The research aims to develop and optimise scientific machine learning approaches for problems in fluid mechanics and hydraulics, including fast flood modelling, alternative Navier-Stokes solvers, and fluid-structure interaction simulations.
You will join a growing PINNs research group in the Faculty of Engineering and Physical Sciences, with access to high-performance computing resources and support in computational fluid dynamics. The project is linked to the University of Southampton, a major UK research-intensive university with strong engineering research activity.
Funding: This is a competition-funded PhD project. Funding opportunities are available for UK and international students. The post mentions Horizon Europe fee waivers, Presidential Bursaries, and studentships that may cover tuition fees and provide a living stipend for top-ranked applicants.
Eligibility: Applicants should have a UK 2:1 honours degree or equivalent in mechanical engineering, aerospace engineering, civil engineering, computer science, physics, mathematics, or a related discipline. Basic programming skills are essential. A background in fluid mechanics, hydraulics, and/or neural networks is desirable.
Application: Apply online for the Research programme (2027/28) in the Faculty of Engineering and Physical Sciences, search for PhD Engineering & the Environment (7175), and include the supervisor name in the application. Applications should include a CV, two academic references, transcripts/certificates, and English language evidence if needed.
Deadline: 2027-05-01.
Funding details
Competition funded PhD project. Funding opportunities are available for UK and international students. Horizon Europe fee waivers may cover the difference between overseas and UK fees for qualifying students. Competition-based Presidential Bursaries may cover the fee difference for top-ranked applicants. Competition-based studentships may cover UK-level tuition fees plus a living stipend for top-ranked applicants. Funding is awarded on a rolling basis.
What's required
Applicants must have a UK 2:1 honours degree or international equivalent in mechanical engineering, aerospace engineering, civil engineering, computer science, physics, mathematics, or a related discipline. Essential requirement: basic programming skills. Desirable: a strong foundation in fluid mechanics, hydraulics, and/or neural networks. English language qualification is required if applicable.
How to apply
Apply online through the University of Southampton application portal. Choose Research, 2027/28, Faculty of Engineering and Physical Sciences, then select full time or part time and search for PhD Engineering & the Environment (7175). Add the supervisor name in section 2 and upload your CV, two academic references, transcripts/certificates, and English language qualification if applicable.
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