Research Fellow

22 hours ago


North Ryde, New South Wales, Australia Macquarie University Full time $120,000 - $180,000 per year
  • Postdoctoral Research Fellow (Level A) base salary $86,970 - $117,108
  • Research Fellow (Level B) base salary $123,435 - $146,044 (appointment level will be based on level of experience)
  • Appointment type: Full-time or part-time (Pro-rata rates apply for part-time appointments), fixed-term position for 2 years (with possibility of extension)
  • Macquarie University Wallumattagal Campus (North Ryde)

Macquarie University is seeking an experienced and enthusiastic Artificial Intelligence (AI) Engineer with a focus on health services research. The ideal candidate will be passionate about applying advanced AI skills to projects aimed at improving health systems and outcomes for aged care residents.

About the Role

Be part of a pioneering national research initiative addressing one of Australia's most pressing aged care challenges: the safe and person-centred deprescribing of medications for older adults in Residential Aged Care (RAC).

The successful candidate will play a key role in developing an advanced AI-augmented digital platform (AiCT-Med) powered by cutting edge machine learning models trained on multiple large, aged care datasets from providers across Australia. The platform is designed to identify deprescribing opportunities, deliver personalised medication recommendations, and support informed decision-making by residents, families, and care teams.

The role will also involve analysing large administrative health datasets and contributing to the preparation of research publications, presentations, and grant applications.

About You

We are seeking an experienced AI Engineer with expertise in machine learning and cloud-based architecture skills to lead the fine-tuning/training, design, development, and integration of the AI components of the AiCT-Med platform.

Candidates from diverse backgrounds in AI, machine learning, natural language processing, or related fields are encouraged to apply. The successful applicant will be interested in working in a multi-disciplinary team and engaging with a broad range of stakeholders. They will continue to develop and expand their own research strengths and interests, particularly as they align with the Centre's research programs.

About Us

The Centre for Health Systems and Safety Research (CHSSR), one of the core research centres within Australian Institute of Health Innovation, has a multi-stream program of research which focuses on investigating the outcomes and safety of health services and a staff of 50. The Centre has particular expertise in assessing the impact of information technologies and investigating the role of electronic health records and decision support in supporting improved health care delivery and health outcomes. The Centre's research team is multi-disciplinary and applies a broad range of research techniques, from RCT designs to direct observations of clinical work.

The Faculty of Medicine, Health and Human Sciences is ambitiously pushing the boundaries of progressive thinking and challenging what's possible to solve some of the big issues of our time, both nationally and on a global scale. Join leading researchers, passionate educators and internationally respected clinicians, united in a mission towards delivering the best patient care. We are a place of bold discoveries and distinctive educational programs that embolden the future leaders of healthcare.

To Apply

To be considered for this position, please apply online and attach your resume and a separate cover letter that outlines how you meet to the selection criteria below. Please specify in the cover letter whether you are applying for full time or part time employment

Selection criteria

  • A PhD in Computer Science or Software Engineering or Computational Statistics, or a related field; or a Master's qualification in a relevant field and/or equivalent demonstrated experience
  • Demonstrated experience working with complex health datasets, including data cleaning, manipulation, and/or data linkage, as well as managing data pipelines (ETL) for analysis.
  • Excellent oral and written communication skills and the ability to liaise effectively with all levels of staff, students, management, health care providers and recipients, and external stakeholders
  • Experience and interest in applied healthcare research and knowledge of the Australian healthcare system
  • Demonstrated experience in contributing to the academic life and administrative tasks of a team with a track record of effective teamwork and leadership
  • Demonstrated advanced programming skills in Python and R (including frameworks such as PyTorch and TensorFlow).
  • Experience using/applying advanced AI techniques including large language models, recurrent neural networks, natural language processing, and ML ensembles in healthcare (or using health datasets)
  • Demonstrated experience in developing/deploying machine learning models or AI solutions, particularly on Microsoft Azure.
  • A strong research track record of peer-reviewed publications
  • Demonstrated ability to contribute to research grant funding applications

Level B Research Fellow (in addition to common criteria above)

  • Extensive experience in AI validation techniques, model testing, and performance optimisation.
  • Proven experience using web frameworks such as RShiny, FastAPI, Flask, or Django to develop and serve LLM-based applications.
  • Experience with MLOps tools (e.g., Docker, MLflow, Kubernetes)
  • Demonstrated success in attracting research funding.
  • Demonstrated experience in leading large health projects (or directing the analysis of large health projects)
  • Proven experience in managing a research team
  • Previous successful experience in supervising higher degree research students
  • Strong publication track record including as lead author on research papers

Desirable (for all levels above):

  • Demonstrated experience in designing/applying LLMs solution in healthcare settings OR/AND
  • Hands-on experience in developing LLM-based applications using frameworks such as Hugging Face Transformers, LangChain, LlamaIndex, etc OR/AND
  • Hands-on experience in deploying machine learning models in cloud-based infrastructure

    are highly desirable.

Please Note: This position requires you to comply with occupational screening, assessment and vaccinations in line with Macquarie University health requirements. You may also have to satisfy Macquarie University that you meet all background checks (including criminal record and qualification checks).

Applications for this position are only being accepted from Australian citizens or permanent residents or people with full working rights.

Specific Role Enquiries: Dr Nasir Wabe, Senior Research Fellow and Team Lead in Aged Care Evaluation Research, Centre for Health Systems and Safety Research, Australian Institute of Health Innovation at

Applications Close: 13th October

Applications need to be submitted through the Macquarie University online recruitment system. Where circumstances such as disability or remote location prohibit your access to our online system please contact Akash on

If you're already part of the Macquarie Group (MQ University, , MQ Health, MGSM), you'll need to apply through your employee Workday account. To apply for this job: Login to Workday and go to the Careers App > Find Jobs.

A Place Where You Belong

At Macquarie, we believe diversity makes us stronger, inclusion drives our success, and belonging inspires us to do our best work. We are proud to foster a community where different backgrounds, identities, and experiences are valued, and where our people are empowered to thrive through supportive leadership, shared responsibility, and a deep commitment to genuine care and respect for our community. Find out more about our vision for a truly inclusive workplace in our Diversity, Inclusion and Belonging Framework.

Flexible Work

At Macquarie, we believe by providing flexibility in when, where and how work is done, we can support our staff to manage their personal commitments, while optimising their work performance and contributions to the University. See how we lead in flexible work to enable an outcome focused and inclusive workplace. To learn more about our culture and hiring process, visit our Jobs at Macquarie page.



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