Bioinformatics data analyst
Scope of the job
The bioinformatics data analyst is responsible for the implementation and development of genomics (and other ‘omics’) data systems at EORTC and is accountable for executing basic to sophisticated data management tasks and for developing sound bioinformatics methods and solutions. The successful applicant needs to possess proficient analytical problem-solving capabilities, experience with genomic data, and strong scientific software analysis and development skills. A strong willingness to learn.
Main responsibilities / Major Activities
- Responsible to provide overall expertise regarding genomic data and related processes.
- Collect and harmonize all genomic data generated at EORTC.
- Develop and run analytic pipelines (NGS panel, WES, proteomics,…) for research and clinical use.
- Apply state of the art bioinformatics methods and develop new analytical tools to perform genomic data analysis
- Post on and release EORTC genomic data from public data depositories (e.g. EGA, TCGA, …) for data sharing.
- Participate in research projects as part of the EORTC Translational research team and in collaboration with clinical scientists and clinical study teams.
- Develop specific R or Python code for genomic data preparation, analysis and sharing.
- Publish R or python package to present at conferences or other venues.
- Ensure successful and timely completion of assigned deliverables.
- Suggest process improvements where appropriate.
- PhD. or MSc. with at least 1 to 3 years of relevant experiences in bioinformatics or a similar discipline with a strong focus on bioinformatics methods and algorithms development.
- Strong interest in biological data analysis and scientific software development.
- Proven experience with manipulating genomic data including NGS (VCF files, plink, and bam files) and willingness to learn more platforms (WES, methylation, protein expression,…)
- Deep knowledge of genomic data analysis and bioinformatics tools and ability to develop new bioinformatics methods to provide solutions.
- Proficiency in R or Python or willingness to learn and improve knowledge in both languages.
- Knowledge of other languages, such as Java or C/C++ would also be an advantage.
- Ability to understand scientific questions.
- Flexible, calm under pressure, highly communicative, and comfortable taking ownership in ambiguous situations.
- Well organized, open-minded, and able to work on different projects in parallel.
- Excellent verbal and written English communication skills.
- Capacity to explain complex technical details in clear and plain language.