APPLY: https://careers.adelaide.edu.au/cw/en/job/514194/grantfunded-researcher-a
(Level A) $75,888 to $102,040 per annum plus an employer contribution of 17% superannuation applies.
Fixed term, full time position available for 24 months.
R software engineer for tidyomics ecosystem and single-cell and spatial omic pipelines Develop the tidyomics ecosystem and scalable data analysis pipelines in R
The position is for a postdoctoral or research-assistant fellow in advanced R programming. Tidyomics (Nature Methods 2024) is an R software ecosystem that enhances the analysis and visualisation of high-dimensional omics data, applying the principles of tidy data analysis, a de facto standard in data science. Given its large adoption, we propose to improve the documentation, robustness, and interoperability of the Tidyomics ecosystem and extend it to spatial profiling technologies.
This exciting position also aims to develop high-performance single-cell and spatial analysis pipelines in R, for high-performance and cloud computing. These pipelines will serve our popular CuratedAtlasQuery database, which deploys the curated and annotated single-cell universe to researchers and institutions.
Key responsibilities: Develop and enhance the tidyomics ecosystem (GitHub: tidyomics), write documentation and create and deliver workshops nationally and internationally. Enhance the pipeline HPCell (GitHub: MangiolaLaboratory/HPCell) and the single-cell knowledge base CuartedAtlasQuery.
To be successful you will need:
Explicitly address each selection criteria below
MSc/PhD in Computational Biology, Bioinformatics, Computer Science, or a closely related field with a strong focus on machine learning and deep learning applications.
Proficiency R, with the ability to handle complex data analysis tasks. Please provide publicly available examples.
A record of research, evidenced by publications in peer-reviewed journals or presentations at significant conferences, particularly in areas related to AI, language modelling, computational biology, bioinformatics, or immunogenomics.
Demonstrable experience in analysing large-scale single-cell genomic data.
Extensive experience in handling, processing, and interpreting large-scale biological datasets, including single-cell RNA-Seq data.
Enjoy an outstanding career environment
The University of Adelaide is a uniquely rewarding workplace. The size, breadth and quality of our education and research programs - including significant industry, government and community collaborations - offers you a vast scope and opportunity for a long, fulfilling career.
We embrace flexibility as a key principle to allow our people to manage the changing demands of work, personal and family life.
In addition, we offer a wide range of attractive staff benefits. These include: salary packaging; flexible work arrangements; high-quality professional development programs and activities; and an on-campus health clinic, gym and other fitness facilities.
Learn more at: adelaide.edu.au/jobs
If you have the talent, we'll give you the opportunity. Together, let's make history.
Applications close 11:55pm, 18 July 2024.
The University reserves the right to close this advertisement before the closing date if a suitable candidate is identified.
For further information
For a confidential discussion regarding this position, contact:
Stefano Mangiola Group Leader - SAiGENCI E: stefano.mangiola@adelaide.edu.au
You'll find a full position description and/or selection criteria below: (If no links appear, try viewing on another device)
The University of Adelaide is an Equal Employment Opportunity employer committed to providing a working environment that embraces and values diversity and inclusion. Female applicants, people with a disability and/or and Aboriginal and Torres Strait Islander people who meet the requirements of this position are strongly encouraged to apply. If you have any support or access requirements, we encourage you to advise us at time of application.
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