CIBIT MPhil Scholarship in molecular imaging – artificial intelligence based/parametric methods at University of Queensland, Canada

Deadline: 30 June 2020

Scholarship Description: 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.

Degree Level: Higher Degree by Research

Available Subjects: Engineering and Computing, Health and Behavioural Sciences, Science and Mathematics

Eligible Nationalities: domestic students or onshore international students are eligible for this scholarship program.

Scholarship Benefits: Scholarship value $34,013 per annum tax-free (2020 rate), indexed annually

Eligibility Criteria:

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

Application Procedure:

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

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

More: https://scholarships.uq.edu.au/scholarship/cibit-mphil-scholarship-molecular-imaging-artificial-intelligence-basedparametric-methods