CSIRO Postdoctoral Fellowship in Computational Genetics applied to Plant Breeding - [Archived Advertisement]
CSIRO Postdoctoral Fellowship in Computational Genetics applied to Plant Breeding
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- Do you have a PhD in quantitative or statistical genetics, biostatistics, computational biology, genomics or plant breeding?
- Do you want to apply your research skills in statistical genetics to provide significant impact in the Australian agriculture sector through the development of improved plant varieties?
- Join CSIRO – Australia’s leading scientific research organisation!
CSIRO Early Research Career (CERC) Postdoctoral Fellowships provide opportunities to scientists and engineers who have completed their doctorate and have less than three years of relevant postdoctoral work experience. These fellowships aim to develop the next generation of future leaders of the innovation system.
CSIRO Agriculture & Food's Cotton Biotechnology Group requires an innovative and forward-thinking computational geneticist/genomics breeder to join the CSIRO Cotton Breeding Program. This CERC Fellow will develop and validate statistical approaches for predicting field performance of cotton plants and breeding lines under rainfed (dryland) production systems using genomic data, as well as assessing the value of incorporating environment, ancestry, and other omic data streams into a genomic selection model. The Fellow will expand upon the conventional phenotype-based breeding approaches currently used by our breeding team to deliver successful cotton cutivars.
Your duties will include:
- Carry out innovative, impactful research of strategic importance to CSIRO that will, where possible, lead to novel and important scientific outcomes including designing and implementing robust statistical approaches and computational pipelines to model the relationships between cotton genotypes and their field-based phenotypes (yield and fibre quality) from rainfed production systems across various growing seasons and environments.
- Recognise and exploit opportunities for innovation and the generation of new theoretical perspectives, and progress opportunities for the further development or creation of new lines of research. This will include the analysis of prediction accuracies of genomic selection models for different rainfed cotton agronomic traits and the refinement of the models or approaches to incorporate environment, pedigree, phenomics and additional -omic data.
- Record, manage, and analyse data using relevant data science techniques. Data streams will include cotton genotype and phenotype data as well as pedigree, environmental, additional phenomic and other omic data sets. This will require close collaboration with the teams generating the data to ensure that it remains relevant for both conventional and advanced genetic approaches to cotton improvement.
- Maintain an in-depth familiarity with recent advances in quantitative genetics and applications of Genomic Selection in different crops and animals that may also be applicable to cotton.
Location: Canberra, ACT
Salary: AU$89k - AU$98k plus up to 15.4% superannuation
Tenure: Specified term of 3 years
To be considered you will need:
- A doctorate (or will shortly satisfy the requirements of a PhD) in a relevant discipline area, such as quantitative or statistical genetics, biostatistics, computational biology, genomics or plant breeding. Please note: To be eligible for this role you must have no more than 3 years (full-time equivalent) of postdoctoral research experience.
- Demonstrated expertise in developing and applying a wide range of analyses for genetic parameter estimation, GWAS, and Genomic Selection, preferably in crop species.
- Demonstrated skills in the handling and analysis of large genotype and phenotype datasets, including the generation of genomic relationship matrices, generation of genomic breeding values using high-dimensional statistical predictive models, and genotype imputation pipelines.
- An understanding of and experience with statistical and machine learning methods to predict quantitative or qualitative traits based on high dimensional genomic data, such as best linear unbiased prediction, penalized regression, Bayesian regression, random forest, support vector machine, neural network and deep learning.
- Evidence of advanced programming skills in languages and statistical software packages relevant to biostatistics and bioinformatics (e.g. R, Python, SAS or equivalent).
For full details about this role please view the Position Description
Applications for this position are open to all candidates. Visa sponsorship will be provided if required.
Appointment to this role is subject to provision of a national police check and may be subject to other security/medical/character requirements.
Flexible Working Arrangements
We work flexibly at CSIRO, offering a range of options for how, when and where you work.
Diversity and Inclusion
We are working hard to recruit people representing the diversity across our society, and ensure that all our people feel supported to do their best work and feel empowered to let their ideas flourish.
At CSIRO Australia's national science agency, we solve the greatest challenges through innovative science and technology. We put the safety and wellbeing of our people above all else and earn trust everywhere because we only deal in facts. We collaborate widely and generously and deliver solutions with real impact.
Join us and start creating tomorrow today!
How to Apply
Please apply on-line and provide a cover letter and CV that best demonstrate your motivation and ability to meet the requirements of this role.
17 June 2022, 11:00pm AEST
- Closing Date:
- 17 Jun 2022
- ACT - Canberra
- AU$89k - AU$98k plus up to 15.4% superannuation
- Work Type:
Plant Biology/Crop Physiology