About the position
The Opportunity:
Together we can do great things. Be part of something bigger. This post is full time, 35 hours per week.
We have a fully funded 3-year position for a highly motivated and skilled post-doctoral researcher in quantitative genetics and epidemiological modelling of infectious diseases in aquaculture. The successful candidate will join a multi-disciplinary international team of aquaculture, genomic and modelling specialists from academia and industry seeking to make scientific breakthroughs in reducing disease transmission and improving disease resilience in farmed fish. As successful candidate you will have the opportunity take a lead role in building and applying the next generation of computational tools to transform future experimental and field study designs, and genetic analyses of infectious disease data to tackle the most pressing disease challenges in aquaculture.
Your skills and attributes for success:
We welcome applications from all over the world that meet the following qualifications:
- PhD, or near completion of a PhD, in a discipline with a substantial quantitative component (e.g. quantitative genetics, statistics, bioinformatics, theoretical biology or physics, applied mathematics).
- Proven research track record in quantitative genetics and genomics, Bayesian statistics/ MCMC and mathematical modelling of disease or other dynamic biological processes.
- Experience in high performance computing, in particular writing efficient computational code for genetic and statistical data analyses and simulation studies.
- Evidenced proficient use of Generative Artificial Intelligence tools in research.
- Excellent verbal and written communication skills evidenced through a track record of research outputs, including publications in peer reviewed scientific journals and presentations at scientific conferences.
- Excellent organisation and time management skills and ability to work independently and in a team.
- Knowledge of aquaculture breeding or farming practices is desirable.
Apply Before: 23/11/2026, 23:59
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