OmniSeq is focused on delivering patients with cancer better access to the power of precision medicine technology and new hope for better outcomes. We provide oncology groups, hospitals and healthcare systems with the first-ever fusion of clinical genomics, immune and a comprehensive information technology solution with easy access to actionable insights about their patient’s condition and available treatment options.
OmniSeq currently offers to the commercial market several cutting-edge clinical cancer tests based on next-generation sequencing (NGS) platforms. We are rapidly growing our product portfolio, and hence have a need for an experienced bioinformatics scientist. They will be the participating in the Bioinformatics perspectives of development and commercialization of the company’s new molecular diagnostic products for cancer.
Work with commercial lab personnel and software engineers focused on using high-throughput data to further develop comprehensive molecular diagnostics tests in a CLIA-certified clinical production environment
- Conduct applied research for commercialization of new products, on novel computational / statistical methods, software tools and databases for analysis of genomes and transcriptomes, with a primary focus on gene expression profiling and disease-associated variant analysis.
- Develop, maintain, and analyze QC metrics to support internal R&D toward NYS CLEP approval of new clinical assays.
- Process, analyze and interpret high volumes of data in a highly controlled and regulated commercial laboratory environment.
- Work independently to prepare and meet timetables, deliverables, and project schedules.
- MS in Bioinformatics, Computational Biology, Genetics, Statistics or similar field required, PhD preferred.
- Demonstrated experience in processing of high-volume genomic data such as microarrays or NGS required, NGS data analysis highly preferred.
- Knowledge of human immune system and cancer biology required, direct experience in cancer research, including a working understanding of computational approaches for cancer genome and transcriptome analysis, highly preferred.
- Prior research experience and academic publications in data analysis for immune profiling and computational methods for immune response biomarker development is a plus.
- Knowledge of commercial and open-source databases and proficiency in utilizing data from public resources such as TCGA, ICGC, COSMIC, HGMD, ClinVar etc. as part of data analysis or method development highly preferred.
- Experience in R, Python, Unix shell scripting or similar, with ability to understand and modify existing code as well as develop new scripts.
- Team oriented with excellent written and verbal communication skills.
- Ability to work in a fast-paced, dynamic, and results-oriented startup environment.
To apply, please forward your resume to email@example.com