Research Scientist - Bioinformatics, CSL

Employer: CSL Limited

Closing date: 21 September 2018

Brief position description: We have an opportunity available for a Research Scientist – Bioinformatics to provide scientific and technical expertise to help answer biomedical questions at the pre-clinical stage of the drug development pipeline using computational methods. In this position, you will expand CSL’s Research capability to mine genomic variants to characterize cell lines as well as to enable patient stratification for better design of clinical trials. Furthermore, you will devise an integrative approach to analyze multiple types of data obtained from in-house and external resources in order to answer key questions in the areas of biomarker discovery and understanding of mechanisms of action of targets, drug candidates and diseases of interest.

You will work closely with Bioinformatics Group members and other Research colleagues to set project objectives and to determine and implement data generation, analysis and software development strategies. You will also work alongside CSL’s external collaborators including spending time in their research laboratories as required to enable alignment of objectives and strategies for computational methods.

Additional Responsibilities include:

Provide input in the design of next-generation sequencing experiments including RNA-seq, DNA-seq, Rep-seq, etc.

Carry out bioinformatic analyses on datasets generated in-house from different NGS and array experiments or collected from external databases and contribute to the interpretation and visualisation of the results.

Establish an in-house capability to utilize genetic and genomic variants in order to improve biomarker discovery, understanding of MoA, patient stratification strategies and prioritisation of indications for drug targets.

Establish an in-house capability to understand the immune repertoire dynamics by analysing Rep-seq datasets generated from patient samples.

Work with in-house software developers to develop fully automated workflows that assist in characterizing transgenic animal models and manufacturing/gene therapy cell lines.

Lead benchmarking and adaptation efforts for new sequencing technologies (e.g. long read and single cell sequencing) in CSL Research in order to answer relevant research questions across multiple drug discovery projects.

Lead efforts to integrate data from public databases (e.g., GTEx, ExAC, ENCODE, UK Biobank) inside CSL Research computational platform and improve upon current data mining practices.

Work with in-house data managers to devise new processes for managing big data and ensure compliance with CSL’s regulatory requirements.

Contribute to CSL’s growing collaboration network with academic laboratories and industry partners locally and globally.


PhD in computational biology, bioinformatics, computer science, biomedical informatics, informatics engineering, molecular biology, genomics or a related discipline with significant computational and biomedical components.

Bachelor’s or Master’s degree in biological sciences (e.g., computational biology, bioinformatics, molecular biology, translational sciences, genetics, etc.)


3+ years of post-doctoral experience in biomedical data analytics in a highly collaborative, interdisciplinary environment in academia and/or industry.

Demonstrated experience in working with genomic variants and genetic information to answer biomedical questions.

Demonstrated experience in eQTL analysis on patient cohorts and/or utilizing eQTL data from public databases to understand mechanism of action of targets, drug candidates or diseases.

Demonstrated experience in applying network biology and pathway analysis algorithms.

Demonstrated experience in using public databases to answer key research questions related to experimental design, biomarker discovery and patient stratification.

Demonstrated experience in working in a Unix-like and high-performance computing (HPC) environment.

Demonstrated experience in developing workflows using various programming languages, e.g., Python, R, CWL, etc.

High quality track record of publications and presentations at national and international conferences.


Experience in applying bioinformatic techniques to enable target identification, biomarker discovery and understanding target/drug mechanism of action studies.

Experience in performing de novo genome assembly using short read and long read sequencing technologies.

Experience in applying machine learning algorithms to interrogate complex datasets.

Experience in developing software using various programming languages, e.g., Java, C++, etc.

Experience in developing web applications for data analytics purposes.

Experience in publishing software packages in open source community projects.

How to Apply:

Applications must address the selection criteria above and include a current CV and covering letter.

Applications close Friday, 21st September, 2018

Job website:

Contact name: Sophie Saba