Postdoctoral Research Fellow (A)

Adelaide University; Adelaide; On-site; AUD 104,000 - 111,000; Full time

Job summary

Adelaide University’s SAiGENCI invites applications for a Postdoctoral Research Fellow in computational and systems biology to lead the mechanistic modelling stream of a cancer research program focused on adaptive resistance to targeted therapy. You will develop and calibrate models linking time-resolved signalling, drug exposure, and tumour dynamics.

The role sits at the Integrative Network Modelling Group within the Computational Systems Oncology program, offering collaboration with clinicians

Qualifications

• PhD awarded or submitted in a relevant field.
• Expertise in developing and applying ODE-based intracellular signalling models.
• Experience with agent-based or logic-based approaches is advantageous.
• Ability to translate biological questions into practical computational frameworks.
• Proven ability to translate complex outputs into biological/clinical insights.

Responsibilities

• Lead the mechanistic modelling stream of the research program.
• Develop and calibrate mechanism models linking time-resolved signalling to PK/PD and tumour dynamics.
• Apply machine learning to pharmacogenomic datasets for predictive biomarker panels.
• Collaborate with biologists and clinicians to design model-informed experiments.
• Mentor quantitative researchers to deepen biological and translational expertise.

Skills

Applied mathematics

Systems biology

Computational modelling

Data analysis

Biological data interpretation

Education

PhD in Computational Biology / Systems Biology / Quantitative discipline

Job description

• Based in the Faculty of health, SAiGENCI


• 12 Months Fixed Term contract (1 FTE) extendable for further 2 years


• Level A - $103,962 - $111,384 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 in computational and systems biology to lead the mechanistic modelling stream of a new research program on adaptive resistance to targeted cancer therapy. The successful candidate will develop and calibrate mechanism models that link time-resolved signalling adaptation to drug exposure (PK), target and pathway modulation (PD), and tumour dynamics, with EGFR- and KRAS-driven non‑small cell lung cancer as the flagship setting. A complementary stream applying machine learning to pharmacogenomic and patient‑derived datasets to build deployable predictive biomarker panels offers additional scope.

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, systems biology, and computational biology, as well as practical experience in dynamic model development and the analysis of large‑scale biological data, who are excited to apply rigorous computational modelling approaches to real biological and biomedical problems. Support and mentorship will be provided to enable strong quantitative researchers to deepen their biological and translational 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:

• PhD (awarded, or submitted and under examination) in Computational Biology, Systems Biology, Applied Mathematics, Biomedical Engineering, or a closely related quantitative discipline, with demonstrated application to biological systems.


• Expertise in developing and applying ODE-based models of intracellular signalling, including model formulation, calibration, parameter identifiability, uncertainty and sensitivity analysis.


• Experience with agent‑based or logic‑based approaches is advantageous.


• Demonstrated ability to translate biological and clinical questions into practical computational frameworks, bridge wet- and dry‑lab environments, and design model‑informed experiments in collaboration with biologists and clinicians.


• Proven ability to translate complex computational outputs into meaningful biological and clinical 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.

Submit your application by 11:30pm Sunday 11 October 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 (quoting reference number 493454):

[phone] | [e-mail]