"Research Fellow in Computational Multiphysics"

About This Opportunity

Join the Computational Multiphysics Laboratory (CML) at UQ’s School of Mechanical and Mining Engineering, where innovation meets impact. As a key member of this dynamic team, you will develop cutting-edge computational models of two-phase flow in fractured media — ranging from fully resolved single-fracture simulations to large-scale discrete fracture network (DFN) upscaling. Your work will directly address high-value industry challenges in energy and resource systems.

CML is internationally recognised for its expertise in computational fluid dynamics (CFD), multiphase and multiphysics flow, and nonlinear solid mechanics, supported by access to world-class high-performance computing infrastructure. You’ll collaborate closely with prestigious research centres including the UQ Gas and Energy Transition Research Centre (GETRC) and the ARC Centre of Excellence for Green Electrochemical Transformation of Carbon Dioxide (GETCO₂).

Under the leadership of A/Prof Christopher Leonardi and Dr Travis Mitchell, the CML has built a 10-year track record of impactful collaboration with major industry players such as Shell, Santos, BHP, Schlumberger, Origin Energy, and Rio Tinto.

Based at UQ’s beautiful St Lucia campus, this is a unique opportunity to contribute to world-leading research that translates directly into practice — shaping sustainable solutions for the energy transition.

Key responsibilities will include:

Research:

• Conduct advanced research in computational fluid dynamics and reservoir modelling, including two-phase flow in fractures, stochastic permeability analysis, and upscaling to fracture networks.
• Deploy large scale simulations using high-performance computing (HPC) and collaborate with academic and industry partners to address real-world energy and subsurface challenges.
• Publish impactful research, support student supervision, contribute to funding proposals, and engage with the broader research community through presentations and collaboration.

Teaching:

• Assist in the delivery of lectures, tutorials and practical classes, where appropriate, as well as the marking of assessment.

Supervision and Researcher Development:

• Support and supervise Honours and Higher Degree by Research students, fostering their academic and professional development.
• Promote a positive research environment through effective mentorship, researcher development, and conflict resolution in line with university policies.

This is a research focused position. Further information can be found by viewing UQ’s Criteria for Academic Performance.

About You

Our ideal candidate will have a passion for and demonstrated ability to solve highly complex problems with a high degree of scientific rigour. The candidate will be able to apply their deep scientific knowledge to solve complex real-world problems, and work with stakeholders to understand their needs and adjust and communicate their approach accordingly to meet any imposed timelines/milestones.

• PhD (or near completion) in Engineering or Applied Science with strong expertise in CFD.
• Proficiency with open-source engineering software and numerical methods such as FEM, FVM, FDM, or LBM.
• Experience running large-scale simulations on high-performance computing (HPC) systems.
• Knowledge of phase-field lattice Boltzmann methods (LBM) for multiphase flow, or ability to quickly acquire it.
• Familiarity with advanced statistical techniques (e.g. GAMLSS), or capacity to gain this knowledge rapidly.
• Proven ability to publish research, write technical reports, and communicate findings clearly.
• Strong collaboration, communication, and time management skills across multidisciplinary teams.
• Willingness to lead research development, support funding applications, and supervise HDR students.