Quentis Therapeutics is a preclinical stage biotechnology company that is translating novel biology into new therapeutic approaches to help more cancer patients benefit from immunotherapy. Based on our deep expertise in endoplasmic reticulum (ER) stress biology and the tumor microenvironment, we are pioneering first-in-class ER stress response modulators to boost the immune system’s ability to fight cancer. Our lead program is a first-in-class IRE1α inhibitor. We are pursuing multiple additional ER stress pathway targets in the tumor micro-environment, as well as in other diseases where ER stress plays an important role.
This is a unique opportunity to join an exciting new biotech company in the heart of New York City that has experienced leadership, a strong scientific expertise and significant funding.
Quentis is seeking a highly skilled and motivated computational biologist to analyze complex, multidimensional datasets such as RNAseq and whole exome sequencing. As a key member of our translational sciences group, the successful candidate will employ both public and proprietary data to drive indication selection, patient selection, and pharmacodynamic biomarker hypotheses. The candidate will also be a key contributor to target and pathway discovery. As our resident expert in computational biology, the successful candidate will be a be driven and enthusiastic self-starter with strong critical thinking skills and a desire to both learn and teach. Additionally, the successful candidate must possess outstanding written and verbal communications skills and be able to work efficiently as an individual and in a team setting in a dynamic, entrepreneurial environment.
• Mine public cancer genomics databases to formulate indication, patient selection and pharmacodynamic hypotheses
• Implement and develop state-of-the-art computational methods and data mining strategies to address key challenges in oncology drug discovery (e.g. drug resistance, combination therapies, harnessing anti-tumor immunity).
• Analyze in-house and public data for pathway (e.g. GSEA) and target discovery
• Work closely with wet-lab scientists to analyze and interpret high-dimensional experimental data (e.g. RNAseq) and collaborate on experimental design
• Use bioinformatics tools to support experimental cell line and animal model selection and characterization
• Serve as key primary company resource for computational biology/bioinformatics
• Organize, analyze and clearly communicate results to team members
• Ph.D. in computational biology, bioinformatics, or related field
• Demonstrated track record of success as evidenced by scientific accomplishments and publications in top-tier journals
• Fluency in one or more programming languages with bioinformatics applications (e.g. Python, R)
• Strong expertise in computational biology/bioinformatics and familiarity with fundamental concepts in molecular biology, statistics, and oncology
• Experience with statistical methods for mining ‘omics data (genomics, transcriptomics, epigenetics, proteomics) from public databases and/or in-house experimental data strongly preferred
• Knowledge of cancer genomics/biology, immunology / immune-oncology, clinical and translational science desired
• Experience mentoring/training wet-lab scientists to perform basic bioinformatic analyses (e.g. applets) a plus
• A passion for scientific discovery and an ability to succeed in a biotech/entrepreneurial fast-paced drug-discovery environment
• Strength in collaboration; able to work effectively across company and academic settings
• Excellent communication, organizational and documentation skills