Published: 14 Mar 2022 1,313 views
This industry funded project will explore the use of AI/deep learning techniques to increase the efficiency of PET acquisition and analysis leading to better diagnostic tools that also improve patient convenience and safety.
Positron Emission Tomography (FDG-PET) imaging is a key biomarker in assessing patients with many neurological diseases including Alzheimer’s and Parkinson’s Disease. While a wide range of PET tracers are available, there are substantial practical impediments to performing multiple PET studies on the same patient including cost, patient inconvenience, and high radiation dose.
This industry-funded project will explore the use of AI/deep learning techniques to increase the efficiency of PET acquisition and analysis leading to better diagnostic tools that also improve patient convenience and safety.
| Application Deadline | Not Specified |
| Type | PhD |
| Sponsor | RMIT University |
| Gender | Men and Women |
Candidates with backgrounds in machine learning and computer vision are encouraged to apply.
To be eligible for this scholarship you must:
• Have first-class Honours or equivalent or a Masters by Research degree in a relevant discipline of science or engineering.
• Provide evidence of adequate oral and written communication skills
• Demonstrate the ability to work as part of a multi-disciplinary research team
• Meet RMIT’s entry requirements for the Doctor of Philosophy
To apply, please submit the following documents to Dr Ruwan Tennakoon and Professor John Thangarajah directly:
Prospective candidates will be invited to submit a full application for admission to the PhD Computer Science (DR221) and potentially an interview.
Scholarship applications will only be successful if prospective candidates are provided with an offer for admission.
For more details, visit RMIT University website.
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