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Vonwiller Research Fellow/ Vonwiller Research Associate

St Leonards, Australia
$86,584 p.a. - $122,830 p.a. + 17% superannuation
Closing date
20 Jul 2024

Job Details

  • Full time, fixed term for 8 months (Maternity Leave backfilled position with potential for contract extension)
  • Opportunity to work at the forefront of coronary heart disease research
  • Base Salary, Level A/B $86,584 p.a. - $122,830 p.a. + 17% superannuation

About the opportunity

Are you excited by the opportunity to apply machine learning techniques to discover new solutions to human health?

Early detection and treatment can prevent the progression of coronary artery disease (CAD) and, consequently, heart attacks. While this can help individuals who display traditional risk factors such as diabetes, hypertension, high cholesterol, and smoking, many people develop CAD over years without the presence of any obvious risk factors. They remain unaware of their susceptibility to the disease and miss out on the opportunity to reduce their risk of a heart attack through taking lifesaving drugs.

CAD Frontiers is an Australian-led, global team composed of clinicians, researchers, data scientists, healthcare and industry leaders with a track record of discovery, innovation and translation. CAD Frontiers is partnering with the Digital Sciences Initiative (DSI) at the University of Sydney to explore the convergence of digital sciences in information, algorithms and machine learning for enhancing the impact and success of diagnostic intervention. By partnering with DSI, CAD Frontiers will build capacity to achieve rapid and demonstrable outcomes in research and commercialisation. The Digital health imaging team within DSI will support CAD Frontiers to improve the understanding, diagnosis and treatment of subclinical disease through developing multimodal AI algorithms that incorporate multiple data sources. AI algorithms for cardiac imaging data, co-designed with multidisciplinary domain expertise, can aid in image understanding and in extracting 'deep' image feature for 'image-omics' - an approach that associates imaging features with complementary -omics data for new biomarker discoveries. This work will revolutionise the clinical approach to early diagnosis of CAD through the discovery of novel biomarkers and the more efficient and affordable analysis of diagnostic imaging data. DSI's established dynamic digital business ecosystem is expected to provide CAD Frontiers with an important interface with start-ups through to multinational industry partners during the commercialisation phase. The partnership aims to maximise industry investment, competitiveness and the likelihood of delivering economic and health outcomes.

We have secured funding through the Vonwiller Foundation to support two Vonwiller researchers to develop novel clinical and data science approaches to CAD diagnostics. Working collaboratively, these two researchers will accelerate research in applied machine learning to ultimately identify the molecular biosignatures of patients with silent atherosclerosis, and the application of these AI algorithms to imaging held in data banks such as BioHEART. Working in an interdisciplinary manner will bring together medical, computer science and engineering mindsets to apply a smart digital solution to a devastating physical problem.

NOTE: These appointments will be at Level A or B dependent on experience skillset decided by the interview panel.

About you

The University values courage and creativity; openness and engagement; inclusion and diversity; and respect and integrity. As such, we see the importance of recruiting talent aligned to these values and are looking for a Researcher who has the following skill sets:

  • tertiary qualifications in Medical Informatics, Computer Science, Machine Learning / Deep Learning / AI (or near completion)
  • PhD qualification along with 1- 2 years' experience post doc completion is required for all Level B appointments.
  • skills in software development including work with Python, C/C++ and the latest machine learning packages
  • prior experience working with medical imaging modalities, in particular coronary artery disease imagery and related biomarker data, is desirable
  • skills in applied machine learning development with medical imaging data using R or Python packages
  • prior experience on recent platforms of omics data such as next generation sequencing or mass spectrometry is desirable
  • high-dimension data analysis experience is desirable
  • demonstrated skills and experience necessary to manage the processes for testing and validation of machine learning algorithms in a clinical environment
  • demonstrated ability to conduct research / scholarly activities as part of a multidisciplinary research team
  • experience managing large volumes of multi-modality data and a demonstrated track record of supporting high quality academic publications and clinical uptake
  • the ability to liaise effectively with both scientific/technical and clinical colleagues
  • ability to assist researchers from other disciplines as well as working with PhD students

To apply

Applications can be submitted via the Apply button at the top of the page. Your application should include a cover letter, a detailed response to the selection criteria (see 'About you'), your CV, and any additional supporting documentation. Your application should clearly indicate which level of appointment you are seeking whether you are seeking a full-time or part-time appointment. However, these appointments will be at Level A or B dependent on experience skillset/qualification criteria as decided by the interview panel.

If you are a current employee of the University or a contingent worker with access to Workday, please login into your Workday account and navigate to the Career icon on your Dashboard. Click on USYD Find Jobs and apply.

For a confidential discussion about the role, or if you require reasonable adjustment or support filling out this application, please contact Faiza Khan at

To keep our community safe, please be aware of our COVID safety precautions which form our conditions of entry for all staff, students and visitors coming to campus.

Pre-employment checks

Your employment is conditional upon the completion of all role required pre-employment or background checks in terms satisfactory to the University. Similarly, your ongoing employment is conditional upon the satisfactory maintenance of all relevant clearances and background check requirements. If you do not meet these conditions, the University may take any necessary step, including the termination of your employment.

As this position is located on an NSW Health site, it is a regulatory requirement to complete compulsory employment checks prior to starting in this position. For more information and instructions, please visit: NSW Health employment requirements.

EEO statement

At the University of Sydney, our shared values include diversity and inclusion and we strive to be a place where everyone can thrive. We are committed to creating a University community which reflects the wider community that we serve. We deliver on this commitment through our people and culture programs, as well as key strategies to increase participation and support the careers of Aboriginal and Torres Strait Islander People, women, people living with a disability, people from culturally and linguistically diverse backgrounds, and those who identify as LGBTIQ. We welcome applications from candidates from all backgrounds.

Copyright The University of Sydney

The University reserves the right not to proceed with any appointment.

Click to view the Position Description for this role.

Applications Close

Saturday 20 July 2024 11:59 PM


The University of Sydney was established in 1850 and is consistently recognised, both locally and internationally, for its outstanding teaching and research excellence. Sydney alumni include Prime Ministers, Governor Generals, Nobel Prize winners and leaders in every field of endeavour.

The University offers a comprehensive range of courses, including a number of disciplines unique in Australia. Teaching is spread across nine different state-of-the art campuses, located across New South Wales.

The University of Sydney’s commitment to excellence in research has resulted in an outstanding record in national competitive funding and underpins an approach to teaching which has won nominations for excellence and resulted in high student satisfaction ratings. The University has 78 research centres and institutes and is home to three ARC Centres of Excellence.

The teaching, research and cultural life of the University is supported by extensive facilities, including the largest library collection in the Southern Hemisphere, the world-class Nicholson Museum of archaeological antiquities, the Macleay Museum of natural history and ethnographic collections and the University Art Gallery. Its outstanding sporting and recreation facilities provide a training centre for students and Olympic athletes.

The University of Sydney is a key member of the Group of Eight Australian major research-intensive universities, and the Worldwide Universities Network.


The University of Sydney has nine official campuses.

1.         Camperdown/Darlington Campus.

2.         Cumberland Campus. Home to the Faculty of Health Sciences (based in Lidcombe).

3.         Mallett Street Campus. Home of the Sydney Nursing School.

4.         Sydney Conservatorium of Music Campus. In Macquarie Street, central Sydney.

5.         Rozelle Campus. Home to Sydney College of the Arts.

6.         Surry Hills Campus. Home to the Faculty of Dentistry.

7.         Camden Campus. Contains facilities connected to the Faculty of Veterinary Science and the Faculty of Agriculture and Environment.

8.         Burren Street Campus. Facilties are currently under development.

9.         Sydney Medical School campuses. These include the School of Rural Health (in Dubbo and Orange), the Royal Prince Alfred Hospital, Concord Hospital, Westmead Hospital, the Children’s Hospital at Westmead, Nepean Hospital, Northern Clinical School, Sydney Adventist Hospital, Broken Hill University Department of Rural Health, and Northern Rivers University Department of Rural Health.


The University of Sydney has 16 faculties.

1. Agriculture and Environment

2. Architecture, Design and Planning

3. Arts and Social Sciences

4. Business (Business School)

5. Dentistry

6. Education and Social Work

7. Engineering and Information Technologies

8. Health Sciences

9. Law (Sydney Law School)

10. Medicine (Sydney Medical School)

11. Nursing and Midwifery

12. Pharmacy

13. Science

14. Sydney College of the Arts

15. Sydney Conservatorium of Music

16. Veterinary Science

Number of Employees

Full-time employees: 7616

For more information, please visit:

Company info
+(61) 2 9351 2222

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