PhD scholarship in materials engineering


Enrolment status New students
Student type Domestic students, International students
Level of study Higher Degree by Research
Study area Engineering and Computing
HDR funding type Living stipend scholarship
Scholarship value $27,596 per annum tax-free (2019 rate), indexed annually
Scholarship duration Three years with the possibility of two 6-month extensions in approved circumstances.
Opening date 5 August 2019
Closing date 1 September 2019

Scholarship description

The successful applicant will be enrolled in the School of Mechanical and Mining Engineering and School of Information Technology and Electrical Engineering working on an Australian Research Council (ARC) Discovery Project to develop new generation of aluminium alloys through big data analytics.  The topics are:

  • Development of a big data analytic knowledge model that is capable of correlating the chemical compositions and processes of aluminium alloys to the mechanical properties.
  • Design and development of new aluminium alloys and the associated processing using the big data analytic model.

The successful candidates will receive training in the physical metallurgy of metals, manufacturing of aluminium alloys, fundamental of big data analytics and machine learning process, and in the required laboratory measurement techniques. 


To be eligible, you must meet the entry requirements for a higher degree by research.

Applications are closed.

Before you apply

If this scholarship has rules, download and read them before applying.

How to apply

To apply for admission and scholarship, follow the link on the upper right of this page. There is no separate application for scholarship because you will be given the opportunity to request scholarship consideration on the application for admission.

Prior to applying, check your eligibility and prepare your documentation.

You should also contact Professor Mingxing Zhang ( to discuss your suitability for this scholarship prior to submitting an application.

Please ensure that you

  1. select 'I am applying for, or have been awarded a scholarship or sponsorship'
  2. enter in the free-text field 'zhang’
  3. list the enrolling unit as the School of Mechanical and Mining Engineering
  4. enter Professor Zhang as your supervisor

Selection criteria

Domestic candidates should have an Honours degree or equivalent in Materials Engineering, mechanical engineering (or related disciplines).  Candidate to work on the big data analytics should have an Honours degree or equivalent in Information Technology.  All candidates must meet the requirements of admission into the PhD program.  Applicants should also be eligible for an Australian government-funded or UQ-founded Scholarship or equivalent.

For the project to be applied for, the student will be required to have and/or develop the following knowledge, skills and attributes: 

  • Sound knowledge of the science and engineering of metals. 
  • Capacity to participate in production of experimental iron, steel and aluminium castings in the University’s experimental foundry, taking part in quality assurance and traceability monitoring. 
  • Well-developed laboratory and practical skills, including safe operation of rotating equipment, accurate measurements and data recording. 
  • Capacity to participate in field trials at remote mine sites, liaising with site personnel and taking detailed on-site measurements of worn multi-specimen test plates. 
  • Ability to operate TEM, SEM and EDS instruments. 
  • Demonstrable commitment to good practice in data management. 
  • Ability to communicate technical concepts and the logical “story” of the project in clearly written English. 
  • Sound knowledge of big data analytics. 

Previous research and/or industry experience in fields such as foundry technology or minerals industry maintenance or big data analytics would be viewed favourably. 

Applications are closed.


Professor Mingxing Zhang
+61 7 3346 8709
Applications are closed.

Terms and conditions

Read the policy on UQ Research Scholarships.

A domestic part-time student with carer’s responsibilities, a medical condition or a disability, which prevents them from studying full time may be eligible for scholarship consideration, on a case by case basis.

Applications are closed.