About Ribon Therapeutics
Ribon is a clinical-stage biotechnology company dedicated to the discovery and development of first-in-class small molecule inhibitors to block the fundamental ability of cancer cells to survive under stress.
Ribon Therapeutics, a clinical biopharmaceutical company focused on targeting stress pathways to develop novel cancer therapeutics, is seeking to hire a computational biology lead. The new hire will work on a variety of bioinformatics projects focused on target identification, drug discovery, translational research, and clinical development. We seek a top-notch contributor to join our culture of transparency, intensity, scientific rigor, and fun!
The successful candidate will lead our computational biology group and serve as an integral member of multidisciplinary drug discovery teams developing novel inhibitors to target cancer.
- Lead the growing computational biology team at Ribon and organize all computational efforts
- Design and perform analyses of NGS cancer exome and transcriptome data, as well as other high-throughput data types using integrative approaches
- Periodically mine public databases to facilitate target selection and biomarker discovery
- Perform custom analyses of -omics datasets designed to answer biological hypotheses
- Apply statistical-based approaches to establish and benchmark predictive models of biological data
- Collaborate with lab scientists as a project team member and provide expertise as a scientific resource
Education and Requirements:
- D. in bioinformatics, computational biology, genetics, or a related discipline + 3-5 years’ experience of applied research in either an academic or industry setting.
- Proficient programming skills utilizing R and python and computational analysis background as well as experience with bioinformatics pipeline development
- Significant experience in the analysis of high-throughput DNA and RNA sequencing data, including alignment, quality assessments, variant calling, fusion discovery, and transcript quantification
- Good understanding of genomic databases and their annotations (GenBank, RefSeq, ENSEMBL, dbSNP, UCSC genome browser, TCGA) and a good understanding of the biology behind gene expression profiling, comparative genomics, and genetic mapping
- Appreciation of the use of statistical methods and mathematical models in the interpretation of biological data
- Ability to effectively interpret and communicate conclusions from complex data is essential
- Ability to work effectively with internal and external collaborators and multidisciplinary teams
- Identify and work with partners/consultants to complement internal bioinformatics efforts
- Ability to work well under pressure and drive projects that affect critical timelines
- Excellent organizational skills and attention to detail
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