Principal Scientist

We are seeking a highly motivated computational scientist to lead translational biomarker discovery at the intersection of human genetics, multi-omics, and AI/ML. In this role, you will identify biomarkers that diagnose disease, predict how it progresses, and anticipate patient outcomes in conditions of impaired cardiac and skeletal muscle function. Bringing together genetic evidence, multi-omics profiling and rich clinical phenotypes, you will work out not only which patients are at risk, but why. Partnering closely with experimental biologists and clinical research, you will carry insights from patients into discovery and from discovery back toward the clinic. This is a hands-on computational leadership role for a scientist excited to apply modern AI/ML to human data in muscle disease. Responsibilities: • Integrate genomic, transcriptomics, proteomic and single cell data to trace how genetic variation drives molecular and cellular changes in cardiac and skeletal muscle disease • Discover and validate diagnostic and prognostic biomarkers of disease onset, progression, and clinical outcomes using omics and longitudinal clinical data from biobanks and patient cohorts • Develop and validate AI/ML methods linking molecular profiles with imaging and clinical phenotypes to define patient subgroups for precision medicine • Investigate disease heterogeneity and genotype-phenotype discordance to uncover modifier pathways and generate mechanistic hypotheses for experimental follow up • Lead translational applications of LLMs and agents (e.g., evidence synthesis, data curation) with appropriate benchmarking Qualifications: • Ph.D. in Computational Biology, Human Genetics, Bioinformatics, or a related field with 6+ years of post-doctoral or industry experience • Strong expertise in analyzing large-scale genomic datasets, including GWAS and sequencing data • Deep expertise in transcriptomics, proteomics, or single-cell analysis with integration across data types • Track record translating human molecular or phenotypic data into disease mechanisms, therapeutic targets or biomarker strategies • Proficiency in R and/or Python, with expertise in study design, batch effects, confounding, longitudinal data and evaluating AI/ML methods • Strong interest in applying AI tools, including LLMs and agents, to translational research (production experience not required) and ability to lead cross-functional projects and mentor scientists Preferred Qualifications: • Experience with population biobanks (e.g., UK Biobank, All of Us) or disease-specific cohorts • Drug discovery experience including biomarker analysis, patient sample studies, or patient stratification • Experience integrating genetic evidence with single cell or tissue-specific expression data • Previous therapeutic area experience in cardiovascular and neuromuscular disease is strongly desired • Experience prototyping LLM-assisted or agentic workflows You don't need to be an expert in every modality or tool. We value depth in a core area, breadth of thinking, and the initiative to generate evidence that changes decisions. To Apply: Please submit your CV, a cover letter outlining your research experience and interests, and a list of publications. Pay Range: The expected salary range for this position based on the primary location of South San Francisco, CA is $202,5000-$236,250. The base pay offered will take into account internal equity and may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. Base salary is just one component of our competitive total compensation package, which includes equity in the form of stock options and/or restricted stock units, comprehensive health, dental, vision, life and disability insurance coverage, 401k retirement benefits with employer match, learning and wellness stipends, and paid time off. Note that benefits are subject to change and may vary based on jurisdiction of employment.