Research Fellow – Data Scientist/Clinical Data Engineer Part-time

Research Fellow – Data Scientist/Clinical Data Engineer

At one of the largest public health schools in the Asia–Pacific, you'll join a vibrant research ecosystem powered by innovation, collaboration and purpose. We embrace diversity, champion inclusion, and empower our people to drive meaningful change.

As part of the Australian and New Zealand Intensive Care Research Centre (ANZIC-RC), you'll work with leading clinicians and researchers tackling real-world challenges in critical care, data innovation, AI and advanced analytics.

We are seeking a talented Data Scientist / Clinical Data Engineer to accelerate digital innovation and research capabilities within the Austin Hospital ICU.

In this 0.5 FTE, Level B research-only role, you will play a key part in transforming clinical data into actionable insights, building digital tools that improve care, and embedding smart research infrastructure directly into the electronic medical record (EMR).

Working closely with Prof Ary Serpa Neto, Austin Health's ICU Research Team, and Monash SPHPM, you'll develop data pipelines, analytics frameworks, AI-driven tools and real-time dashboards that support world-class intensive care research.

What You'll Do

• Build automated data pipelines and extraction tools across Cerner EMR and other clinical databases
• Design digital tools for clinical trials, including automated screening, alerts, randomisation logic and protocol prompts
• Develop predictive models for sepsis, deterioration and ICU outcomes
• Create reproducible analysis frameworks using R/Python, GitHub, Quarto or R Markdown
• Produce real-time dashboards for ICU performance, quality and safety
• Support academic publications, grant proposals and collaborative projects
• Mentor junior researchers and contribute to a thriving data science community

What You Bring

• A postgraduate qualification in Data Science / Computer Science (PhD preferred)
• Strong expertise in Python and/or R, SQL, data engineering and machine learning
• Experience with EMR systems (Cerner highly desirable) and clinical datasets
• Ability to design solutions to complex technical and clinical problems
• Strong communication skills and a collaborative mindset
• Experience in ICU, acute care or clinical research is an advantage

About Monash University

At Monash, work feels different. There's a sense of belonging, from contributing to something ground breaking – a place where great things happen.

We value difference and diversity, and welcome and celebrate everyone's contributions, lived experience and expertise. That's why we champion an inclusive and respectful workplace culture where everyone is supported to succeed.

Some 20,000 staff work for Monash around the world. We have 95,000 students, four Australian campuses, and campuses in Malaysia and Indonesia. We also have a major presence in India and China, and a significant centre and research foundation in Italy.

In our short history, we have skyrocketed through global university rankings and established ourselves consistently among the world's best tertiary institutions. We rank in the world's top-50 universities in rankings including the QS World University Rankings 2026.

Together with our commitment to academic freedom, you will have access to quality research facilities, infrastructure, world-class teaching spaces, and international collaboration opportunities.

Monash supports flexible and hybrid working arrangements. We have a range of policies in place enabling staff to combine work and personal commitments. This includes supporting parents.

To Apply

For instructions on how to apply, please refer to 'How to apply for Monash Jobs'. In your cover letter, please answer the following questions:

• How have your previous data engineering, analytics, or machine-learning projects, particularly those involving clinical or EMR data, prepared you for building automated pipelines, dashboards, and decision-support tools in a hospital environment?
• Can you describe a time when you significantly contributed to a research project or interdisciplinary team, and how your technical expertise supported successful outcomes such as publications, grant proposals, or clinical innovations?
• What examples demonstrate your ability to design solutions to complex data or workflow challenges, and how would you apply this approach to improving ICU research processes, trial automation, or predictive modelling at Austin Health?

Diversity is one of our greatest strengths at Monash. We encourage applications from Aboriginal and Torres Strait Islander people, culturally and linguistically diverse people, people with disabilities, neurodivergent people, and people of all genders, sexualities, and age groups.

We are committed to fostering an inclusive and accessible recruitment process at Monash. If you need any reasonable adjustments, please contact us at hr-recruitment@monash.edu in an email titled 'Reasonable Adjustments Request' for a confidential discussion.

Your employment is contingent upon the satisfactory completion of all pre-employment and/or background checks required for the role, as determined by the University.

Enquiries: Ms. Victoria King, Business Manager, Australia and New Zealand Intensive Care Research Centre, +61 3 9903 0362

Position Description: Research Fellow Data Scientist

Applications Close: Wednesday, 4th March 2026, 11:55pm AEDT

Supporting a diverse workforce