- PhD degree with relevant experience (or equivalent experience) in Bioinformatics, Computational Biology, Systems Biology, Computer Science, Genetics, Statistics, or similar area(s) of study.
- Strong knowledge and hands-on experience of next generation sequencing (NGS) technologies (especially RNAseq, scRNAseq, WGS), multi-omics analysis, network/pathway analysis, statistics and machine learning algorithms.
- Good understanding of molecular & cell biology, immunology, and/or pharmacology/toxicology.
- Proficiency with programming languages (e.g., R, Python).
- In-depth knowledge of public or proprietary bioinformatics applications (e.g., IPA, MetaCore, Cytoscape, PathVisio) and databases (cBioportal, TCGA, GTEx, KEGG, WikiPathways, Reactome, CTD, Open TG-GATEs)
- Familiarity with Unix, Linux, and/or cloud platforms (e.g., AWS, Azure)
- Demonstrated ability to multi-task and work effectively with others in highly collaborative, diverse, and global team environment.
- Strong verbal & written communication and record-keeping skills.