CSIRO Postdoctoral Fellowship in Aquaculture Genetics

CSIRO acknowledges the Traditional Owners of the land, sea and waters, of the area that we live and work on across Australia. We acknowledge their continuing connection to their culture and pay our respects to their Elders past and present. View our vision towards reconciliation .

Role highlights

- Advance aquaculture breeding through genetics, genomics and data science
- Develop innovative tools to guide breeding decisions across generations
- Collaborate on supporting a resilient, sustainable aquaculture industry

About CSIRO

As Australia's national science agency, CSIRO is solving the greatest challenges through innovative science and technology. Many of our iconic innovations were once considered impossible until someone, just like you, joined us and took on the challenge.

CSIRO Early Research Career (CERC) Fellowships provide opportunities to scientists and engineers who have completed their doctorate and have less than three years relevant research experience. These Fellowships aim to develop the next generation of future leaders of the innovation system.

Help shape the next generation of aquaculture breeding . In this postdoctoral role, you’ll combine quantitative genetics, genomics, optimisation and data science to develop breeding strategies for high-performing, resilient and adaptable populations across future generations and diverse production environments . Your research will integrate multi-objective optimisation, Look-Ahead Genomic Selection, genotype-by-environment-by-management modelling and haplotype stacking to guide selection and mating decisions.

Working with a collaborative, multidisciplinary team,



you’ll translate your research into practical decision-support tools that help breeders balance genetic gain, resilience, adaptability, sustainability and genetic diversity. With scientific, technical and industry support, you’ll develop current ideas, build your research capabilities and deliver outcomes with practical value for the aquaculture industry.

Your high-level duties will include:

- Develop and evaluate next-generation quantitative genetic and genomic methods for aquaculture breeding, including multi-trait, multi-environment and G×E×M prediction.
- Develop multi-objective breeding optimisation approaches that balance genetic gain, resilience, sustainability, profitability and genetic diversity.
- Develop and test Look-Ahead Genomic Selection and haplotype-stacking approaches to improve long-term breeding outcomes across generations.
- Build simulation and optimisation frameworks to evaluate breeding strategies under changing environmental, disease, management and production scenarios.
- Integrate genomic prediction, optimisation, mate allocation and look-ahead decision methods into practical breeding decision-support tools.
- Validate the methods using simulated and real aquaculture datasets and assess their transferability across species and production systems.
- Develop reproducible research software,



computational pipelines and technical documentation.
- Publish and communicate research findings, contribute to collaborative research and industry engagement, and support future research and funding opportunities.

Location: On Site inHobart, TAS

Salary: AU$103k - AU$113k per annum (pro-rata for part-time) + 15.4% superannuation

Tenure & work schedule: Specified term of 3 years, Full-time

Reference: 104090

As the successful candidate, you will bring:

- A doctorate (or will shortly satisfy the requirements of a PhD). The doctorate must be in a relevant discipline area, such as quantitative genetics, animal breeding, plant breeding, statistical genetics, genomics, or a closely related discipline.

Please note: To be eligible for this role you must have no more than 3 years (or full-time equivalent) of relevant research experience.

- Strong knowledge of quantitative genetics and/or genomic prediction.
- Demonstrated expertise in statistical modelling and computational analysis.
- Strong programming skills in at least one scientific programming environment such as R, Python or C++.
- Experience analysing large genetic, genomic or biological datasets.
- Develop novel algorithms for multi-stage and long-term breeding decision optimisation.
- Design and implement scalable computational methods capable of analysing large genomic and phenotypic datasets.
- Apply advanced statistical learning, machine learning and artificial intelligence approaches where appropriate to improve prediction and decision-making performance.
- Develop efficient software implementations using modern programming practices, parallel computing and reproducible

📌 CSIRO Postdoctoral Fellowship in Aquaculture Genetics (Hobart)
🏢 Commonwealth Scientific And Industrial Research Organisation
📍 Hobart