Publisher
source

The University of Queensland

Fully Funded PhD in Computational Investigation of Nanoparticle Dynamics Under Electrokinetic Control in Viscoelastic Suspensions The University of Queensland in Australia

Degree Level

PhD

Field of study

Mechanical Engineering

Funding

Fully funded PhD project.

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Country

Australia

University

The University of Queensland

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Keywords

Mechanical Engineering
Chemical Engineering
Materials Science
Mining Engineering
Nanofluid Dynamics
Physics

About this position

Pleased to share a fully funded PhD project at The University of Queensland in the School of Mechanical and Mining Engineering.

The project is titled “Computational investigation of nanoparticle dynamics under electrokinetic control in viscoelastic suspensions” and is being advertised by Christopher Leonardi (Associate Professor at UQ) with collaborators Travis Mitchell, Dan YUAN, and Jun ZHANG from Griffith University.

This opportunity is well suited to students interested in mechanical engineering, materials science, chemical engineering, physics, and computational modelling of complex fluids, nanoparticle transport, electrokinetics, and viscoelastic suspensions.

The post explicitly says the project is fully funded. No deadline or detailed eligibility criteria are provided in the LinkedIn post itself, so applicants should check the project page for the latest requirements and application steps.

To apply, visit the UQ project page, read the project description carefully, and follow the instructions on the study website. If needed, contact the supervisors for clarification before submitting an application.

Funding details

Fully funded PhD project.

What's required

Applicants should be interested in a fully funded PhD project in computational investigation of nanoparticle dynamics under electrokinetic control in viscoelastic suspensions. The post does not list specific academic prerequisites, but a relevant background in mechanical engineering, chemical engineering, materials science, physics, or computational modelling would likely be advantageous.

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