Early detection of neurodegenerative disorders using artificial intelligence

A fantastic opportunity for a PhD student to complete an exciting project which aims to utilize vision deep learning for early detection of neurodegenerative disorders.

About QIMR Berghofer:

QIMR Berghofer is a world-leading translational medical research institute focused on improving health by developing new diagnostics, better treatments and prevention strategies, specifically in the areas of Cancer, Infection and Inflammation, Mental Health and Neuroscience, and Population Health. Based in Herston, Brisbane and working in close collaboration with clinicians and other research institutes, QIMR Berghofer is home to more than 600 scientists, students and non-research staff.

About Genomics, Imaging, and AI Laboratory:

The Genomics, Imaging, and AI Laboratory at QIMR Berghofer is part of the Population Health Program. With a primary focus on neurodegenerative disorders of the eye and brain, the lab employs statistical genetics and artificial intelligence (particularly machine learning) methodologies to advance gene discovery and improve risk prediction for these diseases. The lab also boasts exciting collaborations with industry partners in both clinical and ML analytical domains. 

We are recruiting a highly motivated and organised PhD student to contribute to research studies focused on neurodegenerative diseases affecting the eye and brain, such as glaucoma, dementia, and Parkinson’s disease. Early detection and intervention play a crucial role in managing the risks for developing these conditions. Our ongoing studies utilise machine learning and statistical methods to analyse existing ocular and neuroimaging data. We aim to enhance the prediction of risks associated with these conditions. If you have a passion for research along with expertise in artificial intelligence and data analysis, we invite you to apply for this opportunity.

Main Responsibilities:

●       Develop and implement research projects under the guidance of study supervisors.

●       Analyse large-scale eye and brain imaging data using appropriate machine learning and statistical methods.

●       Interpret results and draw conclusions based on the data analysis.

●       Report to the Principal Supervisor and work from the QIMR Berghofer location.

●       Prepare research findings for publication in peer-reviewed journals.

●       Present research findings at conferences and workshops.

●       Stay updated on current literature and research developments in the field.

●       Effectively manage project timelines, milestones, and deliverables while maintaining detailed records of research activities and progress.

●       Work effectively as part of a research team, and collaborate with other researchers, both within and outside the organization.

●       Ensure that all research activities adhere to ethical standards and compliance requirements.

The Ideal Candidate Would Have:

●       An undergraduate or Master’s degree in machine learning, computer science, physics, data science, bioinformatics, statistics, genetic epidemiology, or a closely related discipline.

●       Proficiency in at least one of the programming languages commonly used in statistics and AI, such as Python, R, or C++.

●       Familiarity with AI frameworks, such as TensorFlow and PyTorch.

●       Ability to apply deep learning algorithms, particularly for computer vision, with application to problems such as regression and classification.

●       Ability to work autonomously as well as within the team.

●       Experience in processing, cleaning, and analysis of large-scale image data is advantages, but not essential.

●       Prior research publications in reputable conferences and journals are advantages, but not essential.

We welcome applications from both national and international candidates.

What We Offer:

●       Tax-free PhD scholarship

●       State of the art facilities

●       Stimulating work setting focused on cutting edge medical research

●       Supportive/collaborative team environment