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.