Role & responsibilities
- Analyze and interpret complex biological data, focusing on Omics (NGS) data analysis including RNA-Seq, scRNA-Seq, and WGS.
- Develop, optimize, and implement novel bioinformatics pipelines using R, Python, and Shell-scripting.
- Work with containerization and workflow management tools like Docker and NextFlow to streamline complex data analysis.
- Support Large Molecule Discovery and biologics research by translating scientific data needs into actionable technical requirements.
- Collaborate with cross-functional teams to manage data capture and reporting utilizing ELN/LIMS platforms (e.g., Benchling).
- Conduct Systematic Literature Reviews (SLR) and targeted literature reviews to generate scientific hypotheses and support biomarker identification.
- Leverage AI/ML tools and statistical analyses to identify trends, patterns, and insights from biological data.
- Work within an Agile/Scrum framework to ensure timely delivery of research informatics projects and UAT coordination Preferred candidate profile
- Masters degree or B.
Tech/B.
E. in Bioinformatics, Computational Biology, Biotechnology, or Life Sciences.
- Hands-on experience or solid academic background in Next-Generation Sequencing (NGS) and multi-omics data analysis.
- Proficiency in programming languages such as Python and R for statistical analysis and data visualization.
- Familiarity with biological databases, sequence analysis tools, and scientific software platforms.
- Excellent analytical, problem-solving, and scientific communication skills.