ROLE RESPONSIBILITIES
Lead the computational target identification and prioritization efforts to provide biological insights and build scientific rational across different disease areas designing, planning and executing projects independently.
Development, implementation and application of algorithms, tools, and methods for Omics data analysis (including but not limited to bulk RNASeq, scRNASeq, spatial transcriptomics, genetics, epigenomics etc.)
Develop computational solutions for quantitative analysis, data integration, and methodology development for internal projects by interacting with experts from multi-discipline.
BASIC QUALIFICATIONS
Ph.D. in Bioinformatics, Computational Biology, Computer Science, Applied Mathematics, or related quantitative field required.
3+ year experience working in matrix cross-functional team with demonstrated experience in design, execution and interpretation of in-vivo and/or in vitro biological experiments generating large-scale NGS datasets.
2+ years relevant experience applying quantitative approaches to addressing biological questions, preferably in a pharmaceutical, biotech or comparable context.
Proficient coding skills in two or more programming languages from Python/R/Java/C#/others is essential. Experience with GitHub is required.
Familiarity with public multi-omics data resources (TCGA, CCLE, Expression Atlas, etc.)
Familiarity with HPC (High-Performance Computing) and cloud computing
Good understanding of ML/DL algorithms and architectures
Proven ability to effectively interact and communicate with multidisciplinary scientists, researchers and non-scientists – internally and externally.
PREFERRED QUALIFICATIONS
In-depth knowledge of biology and demonstrated ability to effectively interface with biologists to communicate/discuss results, hypotheses, and follow-up experiments.
Experience with database management, creating API and data visualization app is a plus.
Experience with Nextflow is a plus.
Experience applying computational and ML/DL approaches to multi-dimensional datasets to deliver insights and hypotheses is a plus.
Other Job Details:
Eligible for Relocation Package: No
Eligible for Employee Referral Bonus: YES
Work Location Assignment: Flexible