Gene regulators are responsible for interpreting the human genome by switching genes on and off at the correct time in the correct cells, and their malfunction is common across many diseases. While our tools to measure and manipulate DNA itself have matured (DNAseq, CRISPR), we lack effective tools for studying gene regulators.
As a result, gene regulators are often passed over in favor of protein families with established experimental approaches, leading to few drug candidates for this target class. There are over 2,200 proteins in this family, yet less than 2% of them are targeted with FDA-approved drugs. Many of these approved drugs were discovered by serendipity, so we instead are pursuing a systematic approach for the discovery and development of gene regulator drugs.
Our platform measures a drug’s ability to disrupt a gene regulator within its natural, non-engineered cellular environment. Furthermore, a single experiment using the platform measures activity for hundreds of gene regulators simultaneously, providing information on in-cell drug activity and specificity in a single experiment. To accomplish this, we combine innovative cell processing with high-sensitivity quantitative proteomics and advanced downstream analytics.
We are seeking a Bioinformatics / Data Scientist to join our team in a full-time role. The analyst will work in a small team setting to develop and improve our platform for drug discovery of gene regulators. We are looking for a technology leader interested in developing and applying new computational approaches to solve complex biological problems. The ideal candidate will thrive working in a fast-paced, innovative, early-stage biotech environment.
Work closely with scientists on the analysis and presentation of proteomics mass spectrometry data produced by our drug development platform Implement, optimize and maintain in-house or open-source analysis pipelines for -omics data Standardize and document data reports for external customers and collaborators Perform exploratory data analysis and collaborate with web-lab scientists to interpret data from technology development and drug development projects Mine literature and public databases for biological insights on potential biomarkers or therapeutical targets Meet production deadlines for data analyses and be able to pivot between multiple projects Accurately document code and analyses in version-controlled repositories and/or an electronic lab notebook Contribute to a rigorously scientific, cohesive and efficient team environment Qualifications
MS or PhD in Bioinformatics, Computational Biology or closely related disciplines 2 years minimum experience in pharmaceutical research or technology development Hands-on experience analyzing large-scale genomics or proteomics data Track record of implementing bioinformatics analysis pipelines Fluent in Bash, R and/or Python, and comfortable with Git Excellent written and verbal communication skills and organizational skills Able to work independently and confidently within a highly-collaborative, fast-paced environment The successful candidate must be self-motivated, a team player, attentive to details, and able to handle multiple projects simultaneously Preferred
Experience in cancer biology Strong data visualization skills Ability to implement machine learning and statistical tools to improve workflows and derive insights from large datasets Working knowledge of cloud computing, particularly AWS
We're looking for people looking to join an interdisciplinary team focused on bringing drug discovery out of the test tube and into the cell. In particular, experts in: