- Full-time, limited to 3 years
- Opportunity to work at the forefront of coronary heart disease research
- Base Salary, Level A/B $97,043 pa – $134,403 pa + 17% pension
About the opportunity
Are you excited about the possibility of applying machine learning techniques to discover new human health solutions?
Early detection and treatment can prevent the progression of coronary artery disease (CAD) and consequently heart attacks. While this can help people with traditional risk factors like diabetes, high blood pressure, high cholesterol, and smoking, many people develop CHD over years with no obvious risk factors present. They are unaware of their susceptibility to the disease and are missing out on the chance to lower their heart attack risk by taking life-saving medication.
CAD Frontiers is an Australian-led, global team composed of clinicians, researchers, data scientists, healthcare professionals and industry leaders with a track record of discovery, innovation and translation. CAD Frontiers is collaborating with the Digital Sciences Initiative (DSI) at the University of Sydney to explore the convergence of digital sciences in the fields of information, algorithms and machine learning to improve the impact and success of diagnostic interventions. Through the partnership with DSI, CAD will build Frontiers’ capacity to achieve rapid and demonstrable results in research and commercialization. The Digital Health Imaging team within DSI will support CAD Frontiers in improving the understanding, diagnosis and treatment of subclinical diseases through the development of multimodal AI algorithms that incorporate multiple data sources. AI algorithms for cardiac imaging data, developed together with multidisciplinary expertise, can help in image understanding and extracting “deep” image features for “image omics” – an approach that combines imaging features with complementary -omics data for the discovery of new biomarkers connected . This work will revolutionize the clinical approach to early diagnosis of CHD through the discovery of novel biomarkers and the more efficient and affordable analysis of diagnostic imaging data. DSI’s established dynamic digital business ecosystem aims to provide CAD frontiers with an important interface to start-ups to multinational industrial partners during the commercialization phase. The partnership aims to maximize industry investment, competitiveness and the likelihood of achieving economic and health outcomes.
We have secured funding from the Vonwiller Foundation to support two Vonwiller researchers in developing novel clinical and data science approaches to CAD diagnostics. Working together, these two researchers will accelerate applied machine learning research to ultimately identify the molecular biosignatures of patients with silent atherosclerosis, and the application of these AI algorithms to imaging in databases such as BioHeart. Through interdisciplinary work, medical, computer science and engineering monuments are brought together to apply an intelligent digital solution to a devastating physical problem.
These appointments are at A or B level, depending on experience.
More information on CAD Frontiers can be found here. More information about DSI’s research-driven mission in medical imaging can be found here.
The university values courage and creativity; openness and commitment; inclusion and diversity; and respect and integrity. As such, we see the importance of recruiting talent in line with these values and are seeking two researchers to do so either one of the following skills:
- University degree in Medical Informatics, Computer Science, Machine Learning / Deep Learning / AI (or about to graduate)
- Software development skills including working with Python, C/C++ and the latest machine learning packages
- Prior knowledge of working with medical imaging modalities, particularly coronary artery disease images and associated biomarker data, is desirable
- University degree in data science, bioinformatics, computer science, applied machine learning or similar (or about to graduate)
- Skills in developing applied machine learning with medical imaging data using R or Python packages
- Previous knowledge of current platforms for omics data such as next generation sequencing or mass spectrometry is desirable
- Experience in high-dimensional data analysis is desirable
From all candidates we are looking for:
- Proven skills and experience required to manage the processes of testing and validating machine learning algorithms in a clinical setting
- Proven ability to conduct research/scientific activities as part of a multidisciplinary research team
- Experience managing large volumes of multimodal data and a proven track record of supporting high-quality academic publishing and clinical uptake
- the ability to collaborate effectively with scientific/technical and clinical colleagues
- Ability to support researchers in other disciplines and collaborate with PhD students
To protect our community, please follow our COVID safety precautions, which form our terms of entry for all staff, students, and visitors coming to campus.
Your employment is conditional on the completion of any pre-employment or background checks required for the role that are satisfactory to the university. Similarly, your ongoing employment is dependent on the satisfactory maintenance of all relevant clearances and background check requirements. If you do not meet these conditions, the university may take any necessary action, including terminating your employment.
Our shared values at the University of Sydney include diversity and inclusion, and we strive to be a place where everyone can thrive. We strive to create a university community that reflects the broader community we serve. We deliver on this commitment through our people and culture programs and key strategies to increase participation and support the careers of Aboriginal and Torres Strait Islander people, women, people with disabilities, people from diverse cultural and linguistic backgrounds and those who identify as LGBTIQ. We welcome applications from candidates from all areas.
How to apply
Applications (including a cover letter, curriculum vitae and other supporting documents, if applicable) can be submitted via the Apply button at the top of the page.
If you are a current university employee or temporary worker with access to Workday, please log in to your working day Account and navigate to the Careers icon on your dashboard. Click on USYD Find Jobs and apply.
For a confidential discussion about the position, or if you require appropriate customization or assistance in completing this application, please contact Linden Joseph or Rebecca Astar, Recruitment Operations, Human Resources at [email protected]
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Click here to view the position description for this role.
Thursday 20 October 2022 23:59