MPhil Scholarship in Molecular Imaging (CIBIT) - artificial intelligence based/parametric methods


Enrolment status New students
Student type Domestic students, International students
Level of study Higher Degree by Research
Study area Engineering and Computing, Health and Behavioural Sciences, Science and Mathematics
HDR funding type Living stipend scholarship, Top-up Scholarship
Scholarship value $34,013 per annum tax-free (2020 rate), indexed annually.
Scholarship duration Two years (24 months) with possible extension up to 28.5 months.
Opening date 10 January 2020
Closing date 9 February 2020


The Australian Research Council Training Centre for Innovation in Biomedical Imaging Technology (CIBIT) is seeking high-achieving graduate students to undertake postgraduate research into the development and application of novel molecular imaging methodologies. We have exciting opportunities to work with world leading academic researchers and industrial partners focused on the development and translation of new molecular imaging methodologies to the clinic. In particular, the candidate will be involved in development of quantitative methods to improve the sensitivity and specificity of PET and MRI-PET imaging.

Projects are available in the following areas:

  1. Application of artificial intelligence and machine learning methods
    • Train a neural network to localise epilepsy foci and assist surgical planning.
    • Develop a generative adversarial network (GAN) to create a CT scan out of a PET, or vice versa.
    • Tumour/organ segmentation directly from sinogram.
  2. Application of parametric methods
  • Validation of Parametric PET Population based input function
  • Validate Patlak with specific antibody tracers
  • Develop a GAN to predict distribution volume images from SUV and CT images.

Applicants should have a background in the physical sciences including disciplines such as biomedical engineering, engineering, information technology, physics or a related field. Applicants should possess analytical and computational skills, including working with equations, simulations and computer programs and an interest in Imaging Modalities and Healthcare IT Solutions.

Successful students will have the opportunity to undertake internships with our industry partners.

CIBIT is a multidisciplinary collaboration between researchers at The University of Queensland’s Centre for Advanced Imaging and partners in the Medical Technologies and Pharmaceutical industry. The purpose of this national Centre is to provide research training in the development and application of novel diagnostics, therapeutics and theranostics (combined therapeutics and diagnostics) in conjunction with industry partners.

CIBIT’s research encompasses two major themes; this project will be specifically related to Theme 2: Harnessing the digital revolution to improve diagnostic imaging cost-effectively.

Further details can be found on the CIBIT website:

The Centre for Advanced Imaging

The Centre for Advanced Imaging (CAI), a strategic initiative of The University of Queensland, is a leading imaging research facility in Australia, and one of a handful in the world. It brings together the skills of a critical mass of researchers and state-of-the-art, world- or Australian-first imaging research instruments including NMR, EPR, MRI, PET, CT, optical imaging and an on-site cyclotron and radiochemistry facilities. CAI hosts the largest Node of the National Imaging Facility (NIF).

CAI conducts research across the spectrum from development of new imaging technologies, analysis of molecular structure, synthesis of MRI and PET biomarkers targeting fundamental biological processes to studies of major diseases affecting a range of organ systems, through to imaging economically significant agricultural animals and plant material, minerals and construction materials.

A multidisciplinary, cohesive student community have come together from all over the globe to CAI to undertake research training.  The Centre has an active student association (STAC) that provides many opportunities for networking and professional development, a supportive mentoring structure that will enhance personal and professional growth, an annual symposium and a well-attended weekly seminar program which attracts high profile National and International speakers.

CAI is committed to supporting the career growth of female researchers and have a number of initiatives to support females in developing and achieving a fulfilling research career at the institute. For more information, please visit our CAI Women in Imaging website.


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

Applications are closed.

Before you get started

If this scholarship has rules, download and read them.

How to apply

To be considered for this scholarship, please email the following documents to Professor David Reutens (

  • Cover letter
  • CV
  • Academic transcript/s
  • Evidence for meeting UQ's English language proficiency requirements eg TOEFL, IELTS

Please note the following: Submitting the above documents does not constitute a full application for admission into The University of Queensland's PhD program. If you are selected as the preferred applicant, you will then be invited to submit a full application for admission. You can familiarise yourself with the documents required for this process on the Graduate School's website.

Applications are closed.


Professor David Reutens
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.

The information you provide in your application is collected for the purposes of (1) assessing your eligibility for this scholarship, (2) selecting scholarship recipients, and (3) administration of the scholarship.  The University of Queensland will disclose the information you provide to CIBIT for the stated purposes.  The University will not otherwise disclose the information to a third party without your consent, unless such disclosure is authorised or required by law.  For further information, please refer to the University’s Privacy Management Policy at

Applications are closed.