Postdoctoral Fellow in Computational Biology and AI Modelling

• Full time fixed term for 2 years at Cobbitty, Camden Campus
• Opportunity to conduct research applying computational biology and AI modelling to plant-pathogen interactions
• Base Salary $113,400 - $121,054 + 17% superannuation

About the opportunity

The School of Life and Environmental Sciences (SOLES) at the University of Sydney is seeking to appoint a Postdoctoral Fellow in Computational Biology and AI Modelling to be based at the Plant Breeding Institute on the University's Camden Campus. SOLES has an international reputation for education and research, with well-funded external research collaborations across industry. The University of Sydney has significant strengths in plant breeding, crop production, plant biology and genetics, and agricultural robotics.

This role offers an exciting opportunity for a highly motivated computational biologist to join a multidisciplinary research team investigating plant-pathogen interactions through integrative computational modelling. You will develop and apply quantitative and data-driven models to study protein interactions and their context-dependent behaviour, linking computational predictions with condition-specific biological responses.

You will have access to large-scale biological datasets, high-performance and cloud-based computing resources, and work in close collaboration with experimental biologists and external computational partners. The successful applicant will demonstrate clear potential to become a leader in their field, with a strong research trajectory focused on computational modelling of molecular interactions and regulatory processes to generate mechanistic insight into host-pathogen biology.

Your research interests will complement and/or enrich existing strengths in the Institute and School in plant breeding, molecular biology, genetics and pathology. You will contribute to current research programs, particularly in resistance gene and avirulence gene cloning, functional studies, and host-pathogen interactions, and articulate a clear vision for collaboration within SOLES, across the University of Sydney and beyond.

Your key responsibilities will be to:

• develop and apply computational models to investigate protein-protein and protein-ligand interactions in plant-pathogen systems
• integrate diverse omics datasets to infer molecular interactions and regulatory processes
• design, implement and maintain reproducible, scalable computational pipelines for large biological datasets
• optimise workflows for high-performance computing (HPC) and cloud-based environments
• collaborate closely with experimental research teams to translate model outputs into testable biological hypotheses
• contribute to scientific documentation, including high-impact publications, research grant applications and reports
• present research findings at national and international scientific conferences.

About you

The University values courage and creativity; openness and engagement; inclusion and diversity; and respect and integrity. As such, we see the importance of recruiting talent aligned to these values and are looking for a Postdoc Research Associate - Computational Biology who has:

• a PhD in bioinformatics, computational biology, systems biology, or a related discipline
• strong proficiency in Python and R for scientific computing and pipeline development
• demonstrated experience in quantitative, statistical or data-driven modelling of biological systems
• experience developing reproducible workflows in HPC and/or containerised environments
• strong analytical capability, scientific ownership and a track record of high-quality research publications
• a clear vision for how your research complements and/or enriches the strengths of the School and Institute
• demonstrated experience in successful collaborative research projects (advantageous)
• excellent written, oral and interpersonal communication skills, with strong time management capability.

Desirable experience

• familiarity with structure-informed or interaction-prediction modelling approaches
• experience integrating computational analyses with experimental or functional validation
• demonstrated experience in protein-centric analyses, including protein interaction networks, signalling pathway modelling, proteomics or protein target screening
• background or demonstrated interest in plant biology or plant-pathogen molecular interactions
• familiarity with molecular cloning techniques.