Csiro Winanga-y Postdoctoral Fellowship in - Canberra, Australia - CSIRO

CSIRO

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Canberra, Australia

1 week ago

Posted by:

Olivia Brown

beBee Recruiter

Description

Acknowledgement of Country:

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

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The Opportunity:

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Do you have a PhD in quantitative/statistical genetics, applied statistics, data science, applied mathematics, computational biology, genomics or plant breeding?**:

Explore new digital based technologies to optimize the design of plant breeding, to more efficiently generate better plant varieties:

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Join the CSIRO Agriculture & Food Breeding Innovations Group for this 3-year postdoctoral fellowship role

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.

We are thrilled to be able to deliver on the commitment we made in our strategy to invest in frontier science with the new CSIRO Agriculture & Food Winanga-y Postdoctoral Fellowship scheme.

The word Winanga-y (pronounced win-na-gnay) is a cultural asset gifted by the Gomeroi Nation in Myall Vale to CSIRO's Agriculture and Food Business Unit to name the Postdoctoral Fellowship Scheme.

Winanga-y means to understand, know, remember, and think.

CSIRO Agriculture & Food's Breeding Innovations Group requires an innovative and forward-thinking computational geneticist to join the team breeding innovations group.

The CERC Fellow will build mathematical and computational approaches to optimize the experimental design in a plant breeding program on the basis of genomic, phenotype and pedigree data, using various modern optimization methods such as combinatorial optimization and Bayesian optimization.

The CERC Fellow will play a leading role on method development and validation, and ultimately will collaborate with the breeders to integrate the methodology into the CSIRO's cotton breeding program to deliver successful cotton cultivars.

Your duties will include:

Recognising and exploiting 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 development of multiple objective optimization algorithms to maximize the experimental design for a cotton breeding program.
Recording, managing, and analysing data using relevant data science techniques. Data streams may include genotype, phenotype, pedigree and environment data. 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.
Communicating complex research findings to the industry collaborators including CSIRO cotton breeders. Also working with breeders to assist them in developing new breeding strategies and decisionmaking tools to enhance the rate of genetic gain in cotton and increase the profitability and sustainability of Australian cotton production.

Location:
Black Mountain, Canberra, ACT

Salary:
AU$92k - AU$101k plus up to 15.4% superannuation

Tenure:
Specified term of 3 years

Reference: 94946

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/statistical genetics, applied statistics, data science, applied mathematics, 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 skills in the handling and analysis of largescale biological datasets such as genomic, phenomic and pedigree data.
Knowledge and experience of mathematical optimization techniques such as in the area of convex, nonlinear, stochastic and dynamic programming, combinatorial and Bayesian optimization.
Evidence of advanced programming skills relevant to scientific computation and statistics (e.g. R, Python, Fortran, C++ or equivalent).

For full details about this role please view the Position Description

Eligibility:

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.

About CSIRO:

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