Parabilis Medicines is a clinical-stage biopharmaceutical company dedicated to creating extraordinary medicines that unlock high-impact protein targets long-considered undruggable. The company has developed a new class of stabilized, cell-penetrant alpha-helical peptides – Helicons™ – capable of modulating intracellular proteins that are inaccessible to traditional drug modalities. Headquartered in Cambridge, Mass., Parabilis is advancing a focused pipeline of multiple first-in-class therapies across both rare and common cancers. Its lead candidate, FOG-001, is the first direct inhibitor of the interaction between β-catenin and the T-cell factor (TCF) family of transcription factors, implicated in colorectal cancer, desmoid tumors, and a range of other Wnt/β-catenin-driven tumors. Parabilis is also advancing investigational degraders of ERG and AR ON for the treatment of prostate cancer, as well as other preclinical programs. Parabilis Inc. is seeking a highly talented and motivated Senior Data Scientist / Cheminformatician to support the platform discovery engine for Helicon TM peptide drugs. Reporting to the Associate Director of Cheminformatics, the candidate will work collaboratively with biologists and chemists, leveraging skills in data science and cheminformatics to enable hypothesis generation and data insights for advancing Fog preclinical drug discovery. You’ll be part of a data science team that is a central pillar of Parabilis’s innovative discovery platform and pipelines targeting “undruggable” genes of major therapeutic interest to patients. Our data science team is an integrated team ranging from computational biology, bioinformatics, computational drug discovery, research informatics and data engineering. We work at the interface of chemistry, biology, clinical and computational sciences, and are responsible for all aspects of data science from building the discovery pipeline to supporting and developing our discovery platform.
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Job Type
Full-time
Career Level
Mid Level
Education Level
Ph.D. or professional degree