We are seeking a highly motivated bioinformatician with industry experience to join our Translational Bioinformatics Immunoscience and Small Molecule Immuno-Oncology team. The successful candidate will help advance Bristol-Myers Squibb’s industry leading IMS and IO pipelines through the strategic application of cutting edge bioinformatics approaches. This team interacts with and influences all aspects at BMS from early discovery through development.
Analyze various -omic-scale data including RNA-Seq, Exome and Whole Genome Sequencing, single cell sequencing, high throughput proteomics, and multiplex flow cytometry in order to nominate novel drug targets, enable patient enrichment strategies, and prioritize combination therapies.
Integrate and mine large-scale external data sets (GEO, TCGA, 1KG, EXAC, Cosmic) to further our understanding of autoimmune diseases and cancer pathogenesis.
Evaluate and analyze genomics data from clinical trials to understand drug mechanisms and patient response. Extract insights and generate hypotheses to be evaluated in future trials and to inform our discovery pipeline.
Collaborate with bioinformaticians, statisticians, biologists, biomarker leads, and clinicians to design experiments. Define and implement statistical/computational analysis plans.
· Ph.D. in bioinformatics, engineering, statistics, physics, molecular biology, genetics, or a similar discipline.
· Five (5) or more years relevant experience in drug discovery research in a pharma or biotech setting.
· Proven track record of independent research under minimal supervision.
· Experience designing complex experiments and statistical analysis plans.
· Strong background in -omic (DNA, RNA, epigenetic, proteomic) data analysis and biological interpretation.
· Experience working with data from clinical trials.
· Solid background in Immunoscience and/or Immuno-Oncology biology.
· Ability to communicate effectively with biologists, biostatisticians and computational scientists.
· Proficiency using R and Bioconductor packages, at least one scripting language (Python, Perl), and SQL.
· Experience working with Linux high performance compute clusters and cloud based computing platforms (Amazon EC2).
· Working knowledge of commercial and publicly available biological databases including NCBI, Ensembl, ArrayExpress/GEO, SRA, TCGA and 1000 Genomes is expected.
· Fluency in NGS experiments and data analysis (e.g. GATK, Cufflinks, SAMtools, BAMtools etc.) is preferred.