University of Melbourne13 followers163 jobs

Research Fellow in Computational & AI Modelling (Infectious Diseases)

GraduateJuniorFull-timeHybridParkville NSW 2337, AustraliaPosted 5 days agoVerified 1 week ago
Pending fitX of Y criteria met

About the job

This Research Fellow job is an exciting opportunity to drive AI-based modelling to tackle infectious disease challenges. By collaborating with leading experimental teams at the Doherty Institute and Cumming Global Centre, you will develop robust computational tools that inform vaccines and therapeutics, making a real-world health impact. The team values diversity, mentorship, and innovation, creating a supportive environment for you to grow as an independent researcher.

You'll be responsible for

🧬

Leading AI-driven computational modelling

Lead AI-driven computational modelling using viral and immunological datasets to identify and prioritise vaccine and therapeutic targets.
🔧

Developing software tools

Develop, test and maintain reproducible software tools and workflows for large-scale infectious disease data analysis.
📊

Collaborating with partners

Collaborate with experimental partners to integrate modelling insights, interpret results and co-author high-impact publications and reports.

Key criteria

🧠

PhD in relevant field

Demonstrated possession of a PhD in engineering or related disciplines.

View

🤖

Machine learning expertise

Proven experience applying machine learning in health or engineering contexts.

View

💻

Programming skills

Experience with Python, R, or Julia for scientific programming.

View

View more

Meet the team

About the company

  • Explore
    • Jobs
    • Companies
    • People
    • Communities
    • Hatch Hotlist 2025
  • Hiring
    • Permanent hires
    • Student placements
  • Resources
    • Blog
    • Community stories
    • Career advice
    • Customer stories
    • Help centre
  • Hatch
    • About
    • Careers
    • Contact
    • Hatch updates
    • Media enquiries
  • © 2026 Hatch
  • Privacy
  • Terms

A meaningful career starts with a match

Get started
Apply on University of Melbourne
You'll apply on an external website
Think you're a good fit?See what the hiring team are looking for

View your fit

5 criteria for this job
PhD in relevant field
Demonstrated possession of a PhD in engineering or related disciplines.

View

Machine learning expertise
Proven experience applying machine learning in health or engineering contexts.

View

Programming skills
Experience with Python, R, or Julia for scientific programming.

View

Data analysis experience
Demonstrated ability to analyze large-scale infectious disease datasets.

View

Interdisciplinary collaboration
Experience working effectively in diverse research teams.

View

Similar jobs

View all
University of Melbourne
University of Melbourne
OPTIMA Postdoctoral Research Fellow, AI in OptimisationParkville, NSW · Full-time
This job is about driving cutting-edge research at the intersection of AI and optimisation within the ARC Training Centre OPTIMA. The impact of this work is significant, as it shapes next-generation AI optimisation tools and fosters industry collaboration. The team thrives on a collegial and multidisciplinary approach, working together to achieve impactful research outcomes.
University of Melbourne
University of Melbourne
OPTIMA Postdoctoral Research Fellow, AI in OptimisationParkville, NSW · Full-time
This job is about driving cutting-edge research in AI optimisation within the ARC Training Centre OPTIMA. The impact of this position is significant, as it involves integrating AI tools into optimisation software and collaborating with industry partners. The team values a collegial and multidisciplinary approach, fostering an environment where everyone can thrive and contribute to meaningful research.
University of Melbourne
University of Melbourne
Research Fellow in Spatial TranscriptomicsMelbourne, VIC · Full-time
This job is about leading computational analyses in the exciting field of endometrial biology and diagnostics through advanced spatial genomics. By collaborating with US-based clinicians and experimentalists, you will have the opportunity to translate groundbreaking discoveries into potential therapeutic and diagnostic targets. The team values a supportive and high-performing environment, fostering collaboration and innovation.
University of Melbourne
University of Melbourne
Research Fellow in Spatial TranscriptomicsMelbourne, VIC · Full-time
This job is about leading computational analyses in the exciting field of endometrial biology and diagnostics through advanced spatial genomics. By collaborating with US-based clinicians and experimentalists, you will have a significant impact on translating discoveries into therapeutic and diagnostic targets. The School of BioSciences fosters a supportive and high-performing environment, encouraging collaboration and innovation.