Summary
The Gibbons Research Group at Trinity College Dublin invites applications for a fully funded 4-year (48-month) PhD studentship titled “Machine Learning for the Design of Additively Manufactured Two-Phase Heat Transfer Surfaces.” Supported by a Royal Society–Research Ireland University Research Fellowship, this project couples physics-informed machine learning and topology optimization with additive manufacturing to design, fabricate, and test high-efficiency phase-change heat transfer surfaces for high-performance computing, data centers, and advanced electronics.
PhD Studentship: Machine Learning for Two-Phase Heat Transfer
Overview Table
| Feature | Details |
| Designation | PhD Student / PhD Researcher |
| Institution | Trinity College Dublin (The University of Dublin) |
| Faculty / Department | Department of Mechanical, Manufacturing & Biomedical Engineering, School of Engineering |
| Research Group | Gibbons Lab (Thermal Fluids and Energy Research) |
| Principal Supervisor | Asst. Prof. Michael Gibbons |
| Funding Body | Royal Society – Research Ireland |
| Stipend | €25,000 per annum (tax-free) |
| Tuition & Fees | Fully covered for both EU and non-EU / International students |
| Duration | 48 months (4 Years, Full-Time) |
| Location | Parsons Building, Trinity College Dublin, Dublin 2, Ireland |
| Application Deadline | 30 September 2026 (reviewed on a rolling basis) |
Designation
- PhD Researcher / Graduate Research Assistant (Full-Time)
Research Area
- Physics-Informed Machine Learning (PIML) & AI-driven computational modeling
- Two-Phase Flows & Flow Boiling
- Topology Optimization
- Thermal-Fluid Science & Heat Transfer
- Additive Manufacturing (3D Printing) of micron-scale surface architectures
- Computational Fluid Dynamics (CFD) and experimental thermal-fluid metrology
Location
Parsons Building, School of Engineering, Trinity College Dublin, College Green, Dublin 2, D02 PN40, Ireland.
Eligibility & Qualifications
Essential Qualifications
- Undergraduate (Bachelor’s) or Master’s degree in Mechanical, Chemical, or Aerospace Engineering, Applied Mathematics, Physics, Computer Science, or a related discipline.
- Strong background in mathematical, analytical, and computational methods.
- Programming experience (preferably in Python).
- Demonstrated interest in thermal-fluid sciences, heat transfer, machine learning, optimization, or numerical simulation.
- Excellent written and oral English communication skills.
- Strong organizational skills and the ability to meet research milestones.
Desirable Qualifications
- Relevant Master’s degree or prior research experience in machine learning/data science.
- Experience with CFD software (e.g., ANSYS Fluent, OpenFOAM, or COMSOL).
- Practical experience in a thermal-fluids laboratory or familiarity with metal additive manufacturing.
- Prior publications in peer-reviewed journals or presentations at international conferences.
(Note: Applicants are not expected to have expertise in every area. Candidates with strong backgrounds in either heat transfer or machine learning who are willing to develop complementary skills are strongly encouraged to apply.)
Scholarship Description & Benefits
- Annual Stipend: €25,000 per year.
- Tuition Fees: Full coverage of PhD tuition and registration fees for the entire 4-year duration (eligible for both EU and Non-EU / International applicants).
- Research & Travel Support: Funding provided for attending international conferences, specialized workshops, and experimental consumables.
- Training & Mentorship: Hands-on training in cutting-edge physics-informed ML, high-performance computing, and experimental two-phase flow facilities within an internationally recognized research group.
How to Apply
The application process consists of two parts:
- Online Form: Complete the online recruitment form.
- Document Submission (Email): Prepare a single, combined PDF containing:
- Detailed Curriculum Vitae (CV).
- Full Academic Transcripts (undergraduate and postgraduate, if applicable).
- A Cover Letter (maximum 1 page) explaining your interest in the project and career aspirations for pursuing a PhD.
- Contact details (including email addresses) of two academic/professional referees.
- File Name Format:
Surname_Firstname.pdf - Submission Email: Send the combined PDF directly to Asst. Prof. Michael Gibbons at
Michael.Gibbons@tcd.ie(orgibbonm3@tcd.ie) with the subject line “PhD Application – Machine Learning for Two-Phase Heat Transfer”.
Last Date for Apply
- 30 September 2026(Note: Applications are evaluated on a rolling basis, and interviews via Zoom/MS Teams may commence prior to the deadline. Early application is advised.)
