Job Description
📋 Description Develop ML methods for biological data (network/graph, single-cell, imaging). Collaborate with experimental/computational biologists and ML scientists. Analyze high-throughput phenotypic screens with rigorous methods. Integrate multiple data modalities (imaging, transcriptomics, genetics, human data). Join a cross-functional team to identify targets and therapies. Hybrid work in South San Francisco HQ, in-person at least three days/week. 🎯 Requirements Ph.D. in computer science, ML, computational biology, systems biology, or related. Extensive hands-on experience developing ML methods for biological data modalities. Experience with network/graph based analysis and modeling techniques. Experience integrating data across modalities (imaging, transcriptomics). Strong programming skills in Python. Commitment to clean code, documentation, and version control. 🎁 Benefits 401(k) with employer matching. Excellent medical, dental, and vision coverage. Open, flexible vacation policy. Paid parental leave of at least 16 weeks; 10 weeks for new parent. Quarterly budget for books and online courses. New hire stipend for home office setup.
