Research Fellow – Data Scientist / Biostatistician

University of Melbourne; City of Melbourne; On-site; AUD 125,000 - 148,000; Full time

Benefits offered by this job

17% superannuation

Salary packaging

Professional development

Health and wellbeing programs

Discounted services

Job summary

The University of Melbourne invites applications for a full-time fixed-term Research Fellow – Data Scientist, Biostatistician, to lead advanced statistical analyses and develop machine learning models for predicting outcomes in ultra high risk youth mental health datasets. This role sits in the Centre for Youth Mental Health and collaborates with NIH/MRFF/CRE-funded projects.

You will manage data wrangling and contribute to peer-reviewed publications while mentoring colleagues across a

Qualifications

• Lead statistical analyses of UHR and related datasets to uncover trajectories and outcomes.
• Develop and evaluate machine learning models for clustering and prediction in youth mental health.
• Data wrangling, cleaning and management using R and associated analytical tools.
• Prepare analysis plans, reports and manuscripts for peer-reviewed publications and grants.

Responsibilities

• Lead statistical analyses of UHR and related datasets, generating robust insights into youth mental health outcomes.
• Develop and evaluate machine learning models for clustering and prediction tasks.
• Undertake data wrangling, entry, cleaning and management using R and associated analytical tools.
• Prepare analysis plans, reports and manuscripts, contributing to peer-reviewed publications and grant applications.
• Engage actively in project meetings, presentations and dissemination activities within Orygen and partner institutions.

Skills

Statistical analyses

Machine learning

R programming

Data wrangling

Team collaboration

Education

Master or PhD in biostatistics, statistics, data science or related quantitative discipline

Tools

R

Job description

Role type: Full-time; Fixed-term until August 2027

Faculty: Medicine, Dentistry and Health Sciences

Department/School: Centre for Youth Mental Health

Salary: Level B: AUD $124,656 - $148,023 p.a. plus 17% super

• Lead cutting-edge youth mental health data science / contribute to NIH-funded global psychosis research / build a strong academic profile
• Apply now to shape predictive models that improve outcomes for young people at ultra-high risk of psychosis.
• Investing in you – 17% superannuation, benefits package including salary packaging, health and wellbeing programs, discounted services, and professional development opportunities.

The University of Melbourne

We take pride in our people, who all contribute to our mission to benefit society through the transformative impact of education and research. Discover more via our website.

Your next career opportunity

You will join the Ultra High Risk for Psychosis team at the Centre for Youth Mental Health.

You will lead advanced statistical and machine learning analyses to uncover trajectories and predictors in young people.

You will contribute to high-impact publications and global collaborations across NIH, MRFF and CRE-funded projects.

What you will deliver

• Lead statistical analyses of UHR and related datasets, generating robust insights into youth mental health outcomes.
• Develop and evaluate machine learning models for prediction, clustering and identification of clinically meaningful subgroups.
• Undertake data wrangling, entry, cleaning and management using R and associated analytical tools.
• Prepare analysis plans, reports and manuscripts, contributing to peer-reviewed publications and grant applications.
• Engage actively in project meetings, presentations and dissemination activities within Orygen and partner institutions.

You may be a great fit if you:

• Hold a Master or PhD in biostatistics, statistics, data science or a related quantitative discipline.
• Demonstrate strong experience applying research methodologies and quantitative analyses to complex health or behavioural data.
• Bring proven expertise in developing and applying machine learning models for clustering and prediction tasks.
• Possess highly developed R programming skills, including data wrangling, modelling, simulation and visualisation.
• Manage competing priorities effectively, meeting project deadlines while working both independently and collaboratively within teams.
• Communicate complex statistical concepts clearly to colleagues and stakeholders with varying levels of technical understanding

For further information please refer to the attached PD.

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 fulfilment, including:

• Build future financial security with 17% superannuation
• Supportive flexible work arrangements underpinned by our commitment to inclusion and well-being
• Career development opportunities, including access to a range of tailored programs, such as Academic Women in Leadership, and learning platforms including LinkedIn Learning
• Progressive, considerate leave provisions to empower your work-life balance and well-being, including leading parental leave, gender affirmation leave and cultural leave
• Salary packaging and access to a range of discounted services including Bupa health insurance, and access to unique cultural and recreational benefits such as discounts for the Melbourne Theatre Company
• Health and well-being services including a leading Employee Assistance Program

For more information check out our benefits page!

Your new team – Centre for Youth Mental Health

You will join the Centre for Youth Mental Health, co-located with Orygen, a world-leading youth mental health organisation.

The Ultra High Risk for Psychosis team brings clinicians, neuroscientists and data scientists together to transform early intervention.

You will work in a collaborative, multidisciplinary environment with strong mentoring, global partnerships and clear academic career pathways.

Be Yourself

The University of Melbourne is an Equal Opportunity Employer and a child-safe organisation. The diversity of our community enriches us all, and we are committed to creating an inclusive and fair workplace where everyone is valued, respected, and empowered to succeed. We welcome applicants from all backgrounds, identities, and experiences. Discover more about Diversity and Inclusion at UniMelb.

We're committed to a barrier-free recruitment process and ongoing workplace support, providing adjustments throughout. We warmly encourage applications from people with disabilities. Learn more about how we support an accessible recruitment process.

Aboriginal and Torres Strait Islander Applicants

We aspire to be the University of choice for Indigenous Australians. Visit our Indigenous staff page to learn more about our investment and support for Aboriginal and Torres Strait Islander staff.

Indigenous applicants are encouraged to connect with our Indigenous Employment & Development team at [e-mail].

Application essentials

• Visit "apply with us" to learn more about the process, including tips and FAQs.
• You must have current valid work rights for Australia. Visa sponsorship is not available for this role.
• A Working with Children Check is required for all positions. If successful, we will guide you through the process and reimburse you.
• Please upload your resume and a cover letter outlining your interest and experience as part of the application process.
• Please upload your responses to the Selection Criteria, found in the Position Description below.

Want to know more?

• For queries related to this specific position, contact Barnaby Nelson at [e-mail]
• For questions related to our recruitment process email Vanessa Phan at [e-mail]
• For recruitment adjustments contact Kim Groizard on [phone] or at [e-mail] (subject: 'Recruitment Adjustments').

Apply today, and join a community that’s shaping the future.

Applications close: 9 October 2026 at 11:55 PM; Melbourne time zone.

Position Description

PD_JR-018490 Research Fellow – Data Scientist, Biostatistician.docx

PD_JR-018490 Research Fellow – Data Scientist, Biostatistician.pdf