Employer:  SAiGENCI (Adelaide University)

Closing date:   18 July 2024

Brief position description:
 R software engineer for tidyomics ecosystem and highly-scalable single-cell and spatial omic pipelines

**(Level A) $75,888 to $102,040 per annum plus an employer contribution of 17% superannuation applies.**

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.

Job website:  http://careers.adelaide.edu.au/cw/en/job/514194/grantfunded-researcher-a

Contact name: Stefano Mangiola

Contact email:    stefano.mangiola@adelaide.edu.au