"Subject Coordinator – Transforming Healthcare with Data and AI"

Role type: Part-time (0.2 FTE) – flexible days and hours; Fixed-term until 31 December 2026
Faculty: Faculty of Medicine, Dentistry and Health Sciences
Department / School: Centre for Digital Transformation of Health
Salary:
Level A - $87,266 - $118,416 p.a. plus 17% super
Level B - $124,656 - $148,023 p.a. plus 17% super

• Transform healthcare education / Engage with diverse professionals / Drive innovative practice change with AI and data science
• Apply now to lead this transformative course in healthcare data science and AI, shaping the future of healthcare innovation.
• Investing in you - benefits package including salary packaging, health and wellbeing programs, discounted services, and professional development opportunities.

Your next career opportunity
Join the Centre for Digital Transformation of Health as a subject matter expert in clinical data science and AI. You'll have the opportunity to teach and refine a cutting-edge course that empowers healthcare professionals, data scientists, and researchers. Collaborate with a dynamic education team, enhance course materials, and contribute to the advancement of healthcare through data-driven innovation.
Your responsibilities will include:

• Update and Refine Course Materials: Review and enhance existing course content to ensure relevance and contemporary delivery.
• Design Workshops and Activities: Develop engaging workshop materials and activities, incorporating feedback and personal expertise.
• Facilitate Guest Speakers: Organise guest speakers for workshops, leveraging personal networks and sector knowledge.
• Provide Student Support: Address student queries promptly via LMS and email, ensuring a supportive learning environment.
• Assess and Feedback: Mark assessments and provide detailed, actionable feedback to students.

You may be a great fit if:
You will have a postgraduate qualification in data science and experience in the Australian healthcare system, with the ability to apply AI and machine learning to healthcare data to support educational delivery.
You may also:

• Have a PhD or equivalent professional experience in data science within a healthcare organisation.
• Have experience with Australian healthcare data, including retrieval, transformation, and analysis.
• Be skilled in applying data science methods, machine learning, and AI to health data.
• Be available for evening workshops in 2026 and able to commit one day per week to the role.
• Have previous teaching experience in higher education and familiarity with tools like Jupyter Notebooks and Google Colab.

What we offer you!
We offer the opportunity to be part of a vibrant community and enjoy a comprehensive range of benefits to support your success and sense of fulfillment, including:

• Supportive flexible work arrangements underpinned by our commitment to inclusion and well-being
• Progressive, considerate leave provisions to empower your work-life balance
• Salary packaging and access to a range of discounted services including Bupa health insurance
• Health and well-being services including a leading Employee Assistance Program

For more information check out our benefits page!
Your new team – Centre for Digital Transformation of Health
The Centre for Digital Transformation of Health is a cross-disciplinary centre that sits in the Faculty of Medicine, Dentistry and Health Sciences, and the School of Computing and Information Systems.
[Detailed description of the centre...]
Join Us and unlock your career potential!
If this role is right for you, please apply with the following documents:

• Resume
• Cover Letter outlining your interest and experience, with responses against the Selection Criteria^ (found in the Position Description). No more than 2 pages.

Learn more about the application process, including tips and FAQs.
For recruitment queries, email Vanessa Phan at hr-careers@unimelb.edu.au. Include the Position Number and Job Title in the subject line.
Position Description: 3536730 Subject Coordinator – Transforming Healthcare with Data and AI.doc