Summary
The Gibbons Research Group at Trinity College Dublin is inviting applications for a fully funded 48-month PhD studentship on Machine Learning for the Design of Additively Manufactured Two-Phase Heat Transfer Surfaces. The project combines two-phase flow, heat transfer, physics-informed machine learning, topology optimisation, and additive manufacturing to develop next-generation heat-transfer surfaces for high-power electronics and data centres.
PhD Studentship – Machine Learning for Two-Phase Heat Transfer
📌 Scholarship Details
| Category | Details |
|---|---|
| Designation | PhD Student / PhD Researcher |
| Research Area | Machine Learning, Two-Phase Flow, Heat Transfer, Thermal-Fluid Engineering, Additive Manufacturing, Topology Optimisation |
| Department | Department of Mechanical, Manufacturing & Biomedical Engineering, School of Engineering |
| Research Group | Gibbons Research Group |
| University | Trinity College Dublin, the University of Dublin |
| Location | Parsons Building, Trinity College Dublin, College Green, Dublin 2, Ireland |
| Supervisor | Assistant Professor Michael Gibbons |
| Duration | 48 months |
| Status | Full-time (~38 hours/week) |
| Funding | €25,000 per annum stipend + PhD registration fees |
| Funding Source | Royal Society–Research Ireland University Research Fellowship |
| Last Date to Apply | Open until a suitable candidate is identified |
🔬 Research Area
The PhD will focus on developing physics-informed machine-learning models to predict the performance of flow-boiling surfaces and integrating these models with topology optimisation for the intelligent design of phase-change heat-transfer surfaces.
Key research areas include:
- Two-phase flows and flow boiling
- Heat transfer and thermal-fluid science
- Physics-informed machine learning
- Machine learning and computational modelling
- Topology optimisation
- Additive manufacturing
- Advanced heat-transfer surface design
- Computational fluid dynamics (CFD)
🎓 Eligibility / Qualification
Essential:
- Honours undergraduate degree in a relevant discipline such as:
- Mechanical Engineering
- Materials Science
- Applied Mathematics
- Physics
- Computer Science
- Strong mathematical and analytical abilities
- Programming experience, preferably Python
- Demonstrable interest in heat transfer, machine learning, optimisation, or computational modelling
- Ability to plan, prioritise and meet deadlines
- Fluent English with excellent written and oral communication skills
Desirable:
- Relevant Master’s degree
- Experience in machine learning/data science or numerical methods
- Background in heat transfer, fluid mechanics or thermodynamics
- Experience with ANSYS Fluent, OpenFOAM or COMSOL
- Optimisation experience
- Thermal-fluid laboratory experience
- Familiarity with additive manufacturing
- Peer-reviewed publications or international conference presentations
Candidates do not need to possess every listed skill. Applicants with strong expertise in either heat transfer or machine learning who are willing to develop skills in the other area are particularly encouraged to apply.
💼 Job Description
The successful PhD researcher will:
- Conduct research into two-phase flows and flow boiling.
- Develop physics-informed machine-learning models for heat-transfer surface performance.
- Integrate machine learning with topology optimisation.
- Investigate intelligently designed phase-change surfaces manufactured using additive manufacturing.
- Contribute to computational and/or experimental thermal-fluid research.
- Work collaboratively with PIs and postgraduate researchers within a multidisciplinary research team.
- Present research findings and contribute to publications and conferences.
- Participate in structured training, external courses and research-group activities.
💰 Funding & Benefits
- €25,000 annual stipend
- PhD registration fees covered
- 48 months of funding
- Full-time PhD research position
- Training in machine learning, thermal sciences and related computational/experimental techniques
- Opportunity to work within an internationally recognised research group at Trinity College Dublin
📝 How to Apply
The application consists of two parts:
1. Complete the online application form:
PhD Application Form
2. Email one combined PDF containing:
- CV
- Academic transcripts
- Short cover letter (maximum 1 page) explaining:
- Why you are interested in the project
- What you hope to gain from a PhD
- Names and contact details, including email addresses, of 2 referees
Name the PDF in the format:
Surname_Firstname.pdf
Send the completed PDF to:
Shortlisted candidates will be invited to a Microsoft Teams or Zoom interview with Assistant Professor Gibbons and the research team.
📅 Last Date for Apply
Open until a suitable candidate is identified.
⚠️ Early application is recommended, as applications may close once a suitable candidate has been selected.
🏛️ About Trinity College Dublin
Trinity College Dublin is Ireland’s leading university and a major international centre for education, research and innovation. The university hosts around 18,000 undergraduate and postgraduate students and has a highly international research community.
Research Group: Gibbons Research Group
University: Trinity College Dublin
