Ucsf Medical Center - San Francisco, CA
posted 3 months ago
The I-SPY EOP Research Data Analyst position at the University of California, San Francisco (UCSF) is a full-time role that requires a seasoned research professional with extensive experience in statistical analyses and research software programming techniques. The primary focus of this role is to provide technical expertise in planning and performing correlative analyses of biomarker and clinical data from the endocrine optimization pilot EOP I-SPY 2 sub-study trial, as well as other I-SPY trials. This sub-study evaluates the feasibility of neoadjuvant endocrine therapy with or without novel agents in patients who are molecularly low risk but clinically high risk for HR+HER2- breast cancer. The role involves collecting various biomarkers, including expression-based, imaging, circulating, and pathology-based data, to perform correlative studies. Additionally, organoids will be generated from tissue samples for advanced analyses such as single-cell sequencing and in vitro treatment sensitivity assays. The incumbent will be responsible for providing bioinformatics and statistical support for the EOP and other I-SPY studies, working on projects that assess the correlation between biomarkers evaluated at baseline and longitudinally to characterize patient responses to endocrine therapy. This includes collaborating with trial investigators and the sponsor's biometrics team to develop and execute bioinformatics and statistical analysis plans that leverage biomarker and clinical data to address clinically relevant questions. The role also involves generating reports and presentations to communicate findings to a diverse audience, including clinicians, bioinformaticians, statisticians, and patient advocates, as well as supporting the preparation of manuscripts based on research findings. The position requires daily communication with various stakeholders to ensure the quality and timely execution of proposed analyses. A strong background in translational biomarker research and applied bioinformatics is essential, particularly expertise in methodologies for high-dimensional biomarker association analyses with different types of outcomes. Experience with longitudinal biomarker data analyses, next-generation exome sequencing data analysis, and single-cell sequencing data analysis is preferred. The final salary and offer components are subject to additional approvals based on UC policy, and placement within the salary range will depend on factors such as work experience and internal equity.