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- Tasks: Develop AI-driven methods to speed up fluid dynamics simulations for engineering applications.
- Company: University of Birmingham, leading in computational modelling and Defence research.
- Benefits: Fully funded PhD with a £25k tax-free stipend and covered fees.
- Why this job: Join a cutting-edge project that combines physics, computation, and AI to tackle real-world challenges.
- Qualifications: Open to all; prior experience in AI or CFD is a plus but not required.
- Other info: Gain hands-on experience with industry-standard tools and valuable skills for future careers.
The predicted salary is between 25000 - 25000 £ per year.
This fully funded PhD opportunity sits at the cutting edge of computational modelling, artificial intelligence, and national-priority Defence research. Hosted at the University of Birmingham and funded through a UK Defence programme, the project tackles one of the most important challenges in modern engineering: how to dramatically accelerate high-fidelity computational fluid dynamics (CFD) simulations using machine learning.
CFD is a cornerstone of engineering across energy, aerospace, automotive, chemicals, and Defence, but its computational cost can be prohibitive. Many realistic simulations take weeks or even months to run, making detailed sensitivity analysis, uncertainty quantification, and rapid design exploration effectively impossible. This project aims to change that.
By integrating state-of-the-art AI and machine-learning techniques with established CFD solvers, the student will help develop new approaches that markedly reduce simulation times while retaining physical accuracy and trustworthiness. The initial application focuses on complex, high-speed gas-flow problems, but the tools and methods developed will be broadly transferable across sectors and disciplines.
The core ambition is to create AI-accelerated simulation pipelines that allow engineers and scientists to explore design space, risk, and uncertainty in ways that are simply not feasible today. A defining feature of this PhD is the level of support and training provided. You will be part of a large, supportive, and highly interdisciplinary research team spanning engineering, applied mathematics, computer science, and data science.
While prior expertise in the areas of AI and/or CFD is beneficial, it is not expected. Instead, the project is designed to actively support the student in developing powerful, in-demand skills in CFD, numerical modelling, machine learning, and scientific programming. You will gain hands-on experience with industry-standard tools (such as OpenFOAM), alongside unique modelling and AI frameworks developed at the University of Birmingham and used in high-impact academic and industrial research.
The training provided will provide a valuable foundation for your future career - advanced modelling and AI skills are now foundational across engineering, technology, and data-driven industries. Graduates with deep expertise in simulation-accelerated AI are exceptionally well positioned for careers in Defence, aerospace, energy, advanced manufacturing, software, finance, and beyond, whether in industry, national laboratories, start-ups, or academia.
If you are excited by combining physics, computation, and AI to solve real-world problems of national importance, and want to graduate with a skillset that will remain valuable for decades, this project offers a rare and powerful opportunity.
Funding notes: The successful candidate will receive a full EPSRC stipend, plus an additional £5k top-up from the industrial sponsor, equating to a tax-free annual income of £25k. All fees for the PhD will also be covered by the sponsor, with additional funding to support travel and other expenses.
For more information please contact Prof. Kit Windows-Yule at c.r.windows-yule@bham.ac.uk
PhD Studentship: Machine Learning approaches to improve the efficiency of fluid dynamics simulations in Birmingham employer: University of Birmingham
Contact Detail:
University of Birmingham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land PhD Studentship: Machine Learning approaches to improve the efficiency of fluid dynamics simulations in Birmingham
✨Tip Number 1
Network like a pro! Reach out to current PhD students or faculty members at the University of Birmingham. They can give you insider info about the programme and might even put in a good word for you.
✨Tip Number 2
Show off your passion for AI and fluid dynamics! When you get the chance to chat with potential supervisors or during interviews, make sure to highlight any relevant projects or experiences that showcase your enthusiasm and skills.
✨Tip Number 3
Prepare for technical discussions! Brush up on your knowledge of machine learning and CFD concepts. Being able to discuss these topics confidently will set you apart from other candidates.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets the attention it deserves. Plus, we’re always looking for passionate individuals who want to make a difference in the field.
We think you need these skills to ace PhD Studentship: Machine Learning approaches to improve the efficiency of fluid dynamics simulations in Birmingham
Some tips for your application 🫡
Show Your Passion: When writing your application, let your enthusiasm for machine learning and fluid dynamics shine through. We want to see why you're excited about this PhD opportunity and how it aligns with your career goals.
Tailor Your CV: Make sure your CV highlights relevant skills and experiences that relate to AI, CFD, or computational modelling. We’re looking for candidates who can demonstrate their potential to thrive in this interdisciplinary research environment.
Craft a Compelling Cover Letter: Your cover letter is your chance to tell us your story. Explain why you’re the perfect fit for this project and how your background prepares you for the challenges ahead. Be specific about your interests and any relevant projects you've worked on.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the easiest way for us to keep track of your application and ensure it gets the attention it deserves. Plus, it shows you’re serious about joining our team.
How to prepare for a job interview at University of Birmingham
✨Know Your Stuff
Make sure you brush up on the fundamentals of fluid dynamics and machine learning. Familiarise yourself with key concepts, especially how they relate to computational modelling. Being able to discuss these topics confidently will show your genuine interest in the PhD project.
✨Show Your Passion for Problem-Solving
This project tackles significant challenges in engineering, so be prepared to share your thoughts on how AI can improve CFD simulations. Think about real-world applications and be ready to discuss any relevant experiences or projects that demonstrate your problem-solving skills.
✨Ask Insightful Questions
Prepare a few thoughtful questions about the research team, the tools you'll be using, or the training provided. This not only shows your enthusiasm but also helps you gauge if this opportunity aligns with your career goals. It’s a two-way street!
✨Highlight Your Interdisciplinary Skills
Since this role involves collaboration across various fields, emphasise any experience you have in working with different disciplines. Whether it’s engineering, computer science, or data science, showcasing your versatility will make you a standout candidate.