NHMRC Externally Funded Research Fellow (A)
Job no: 493185
Work type: Fixed term - Full-time
Location: Adelaide CBD
Categories: Level A
- Based at SAiGENCI, College of Health
- 36 Months Fixed Term contract (1 FTE)
- Level A - $102,024 - $109,307 per annum plus an employer contribution of 17% superannuation applies
At Adelaide University, we create the opportunities you need to achieve your ambitions – because when you thrive, we thrive.
We are seeking a highly motivated Postdoctoral Research Fellow with strong expertise in computational and systems biology to lead the integrative modelling components of our NHMRC-funded project. This role is central to redefining the STAT3 signalling dogma by mapping its time-, stimulus-, and cell lineage-resolved interactome using cutting-edge technologies, including unbiased proteomic mapping (APEX2), iPSC-derived lineages, and functional genomics (CROP-Seq). The successful candidate will be responsible for the integrative analysis of large-scale multi-omics datasets and the development of predictive computational models to identify complex regulatory mechanisms of STAT3 signalling networks and pathway rewiring in varying biological contexts.
Work that matters
The Integrative Network Modelling Group within the Computational Systems Oncology program at SAiGENCI sits at the intersection of mathematics, computation, and cancer biology. We develop mechanistic, predictive models of cellular decision-making to address both fundamental and translational challenges in oncology, including drug resistance, pathway rewiring, and the discovery of new therapeutic vulnerabilities. Beyond cancer specifically, our research explores broader questions regarding cell fate decisions, the hidden dynamics of complex signalling networks, and their underlying regulatory mechanisms.
Our approach is deliberately cancer-agnostic, focusing on principles that generalize across various tumour types while exploring the governing and design principles that dictate complex signalling behaviour. A defining feature of our group is the tight integration of dynamic network modelling with experimental and clinical insight, enabling us to move beyond mere description and toward robust, actionable prediction. If you are a talented systems biologist driven by both curiosity and discipline, we want you on our team!
The team
The role is ideal for candidates with a strong background in applied mathematics, physics, engineering, or computational biology who are excited to apply rigorous modelling approaches to real biological and biomedical problems. Support and mentorship will be provided to enable strong quantitative researchers to deepen their biological expertise over time.
Visit the AU website to learn more about SAiGENCI
Our people
Our people are guided by purpose, curiosity and a commitment to lifelong learning. We embrace authenticity, innovation and collaboration, and harness diverse thinking in our pursuit of excellence. This role is ideal for someone who thrives in a collaborative and innovative environment with international visibility, and high-impact, conceptually driven cancer research.
Learn more about our people, what we stand for and what we offer at Careers at AU.
Experience
To thrive in this role, you will likely have the following skills and experience:
- Strong background in applied mathematics, systems biology, computational biology, or a related quantitative discipline, with an interest in solving real-world biological and biomedical challenges.
- Expertise in computational modelling approaches, including network-based, mechanistic, and/or AI/ML frameworks for analysing complex biological systems.
- Experience identifying key signalling network mechanisms, predictive biomarkers, and biological design principles from large-scale datasets.
- Proven ability to develop and implement robust computational pipelines for integrative analysis of omics and mass spectrometry data, particularly interactomics and post-translational modification mapping.
- Demonstrated success translating complex clinical and biological questions into practical computational biology solutions.
- Strong collaborative track record working across dry-lab and wet-lab environments, partnering with experimental biologists and clinicians to generate biologically meaningful insights.
Our commitment to inclusion and diversity
We are committed to fostering a culture of inclusion where diversity is celebrated and everyone feels respected and valued. Adelaide University is an equal opportunity employer, committed to creating a safe, inclusive, and equitable workplace where everyone can thrive. We strongly encourage applications from Aboriginal and Torres Strait Islander peoples, people with disability, and people of all ages, genders, cultural backgrounds, sexual orientations, and gender identities. We are committed to supporting flexible working arrangements and providing reasonable adjustments throughout the recruitment process.
Build on your career with Adelaide University now
Applying is simple. Simply click on the Apply Now button and upload:
- your current CV
- a cover letter that tells us why you’re excited about the role
Submit your application by 11:30pm Thursday 16 July 2026
The University reserves the right to close this advertisement before the closing date if a suitable candidate is identified.
Please note that the role description is not attached to this advertisement as it is currently being finalised.
For further information about this opportunity, please contact:
Dr Sungyoung Shin
Emerging Leader
SAiGENCI – College of Health
Adelaide University
sungyoung.shin@adelaide.edu.au
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Application close: Cen. Australia Standard Time
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