Machine Learning / Data Scientist
Summary: FogPharma, a biopharmaceutical company based in Cambridge, Mass., is pioneering the development of Helicon™ therapeutics to precisely target intracellular disease drivers. They are seeking a Scientist/Senior Scientist in Machine Learning to contribute to their Computational Drug Discovery group, focusing on Helicon™ stapled-peptide drugs. The role involves developing and supporting machine learning models for hit identification, screening library designs, drug-target assessments, and advancing drug-pipeline projects towards clinical trials. The successful candidate should have a PhD or MS with 2+ years of experience in machine learning, proficiency in Python and relevant ML libraries, and experience in life sciences and biopharmaceutical companies. Strong communication, collaboration, and leadership skills are essential, along with familiarity with cloud computing environments and peptide-related experience. FogPharma values creativity, patient focus, execution orientation, and humility, and promotes a diverse and inclusive work environment.
About the Company
Description: FogPharma was born from the scientific and entrepreneurial vision of founder Greg Verdine, a pioneer in the discovery and development of new drug classes that “drug the undruggable.” FogPharma’s cell-penetrating mini proteins (CPMPs) are a broad new class of medicines that can drug targets beyond the reach of conventional therapeutics. Together with world-leading experts and collaborators in cancer biology and therapy, our team is building a drug discovery powerhouse having passion, knowledge, and creativity to develop fundamentally new cancer treatments. FogPharma derives financial support from a unique syndicate of extraordinary private and institutional investors. FogPharma’s network of friends includes our founders, employees, investors, advisors, collaborators, and cancer patients; all working together to pioneer a unique approach toward conquering cancer.
Industry: Health Tech
Company Size: Medium (51-250 employees, $10M-$50M revenue)