Postdoctoral fellow

UCSF, Division of Cardiology, Pirruccello Lab; San Francisco (CA); On-site; USD 60,000 - 70,000; Full time

Job summary

The Pirruccello Lab at UCSF/CVRI is seeking a postdoctoral fellow to advance research at the intersection of cardiovascular genetics, deep learning, and epidemiology.

The fellow will generate and refine cardiac and aortic valve phenotypes from imaging data, apply them at biobank scale, and develop genetic and epidemiological models to translate findings into broader clinical and research contexts.

Qualifications

• PhD in a relevant field completed or anticipated.
• Experience with deep learning methods applied to biomedical data is preferred.
• Strong background in statistics and epidemiology is required.

Responsibilities

• Conduct cutting-edge research at the intersection of cardiovascular genetics, deep learning, and epidemiology.
• Generate and refine cardiac and aortic valve phenotypes from imaging data at biobank scale.
• Apply statistical genetics, deep learning, and classical statistics to investigate relationships with phenotypes.
• Disseminate findings through high-impact publications and national/international conferences.

Skills

Deep learning

Cardiovascular genetics

Epidemiology

Statistical analysis

Education

PhD in a relevant field

Job description

Position Description

The postdoctoral fellow will engage in cutting-edge research at the intersection of cardiovascular genetics, deep learning, and epidemiology. The Pirruccello Lab at UCSF/CVRI is interested in understanding the drivers of normal variation in aortic valve hemodynamics. The postdoctoral fellow will use computer vision and deep learning tools to generate and refine cardiac and aortic valve phenotypes to apply at biobank scale (~100,000 imaging studies from UK Biobank and thousands of clinically indicated imaging studies from UCSF); to investigate genetic and epidemiological relationships with these phenotypes; and translate discoveries into ECG-based, proteomic, and classical statistical models. The postdoctoral fellow will utilize common-and rare-variant statistical genetics, deep learning, and classical statistics. It is expected that the postdoctoral fellow will independently devise experiments, analyze complex datasets, apply for and obtain extramural funding, disseminate findings through high-impact publications, and present preliminary data at local conferences and national/international scientific meetings. This position emphasizes comprehensive professional development, with opportunities to apply for independent research funding, participate in cross-disciplinary seminars, and gain experience in deep learning and genetics.

Position Qualifications

Postdoctoral scholars are defined as \"a person professionally conducting research after the completion of their doctoral studies\" (typically a PhD). The goal of a postdoctoral research position is to pursue additional research, training, or teaching to have better skills to pursue a career in academia, research, or any other fields. Postdocs often, but not always, have a temporary academic appointment, sometimes in preparation for an academic faculty position. They continue their studies and/or carry out research and further increase expertise in a specialist subject, including integrating a team and acquiring novel skills and research methods. Postdoctoral research is often considered essential while advancing the scholarly mission of the host institution; it is expected to produce relevant publications in peer-reviewed academic journals or conferences. Postdocs may not perform any clinical duties. The NIH definition of a postdoc is an individual who has received a doctoral degree (or equivalent) and is engaged in a temporary and defined period of mentored advanced training to enhance the professional skills and research independence needed to pursue his or her chosen career path.

Research Environment / Training Context

Postdoctoral scholars shall not perform any clinical duties and shall not have any patient contact. The postdoctoral fellow will engage in cutting-edge research at the intersection of cardiovascular genetics, deep learning, and epidemiology. The Pirruccello Lab at UCSF/CVRI is interested in understanding the drivers of normal variation in aortic valve hemodynamics. This position emphasizes comprehensive professional development, with opportunities to apply for independent research funding, participate in cross-disciplinary seminars, and gain experience in deep learning and genetics.

UC San Francisco seeks candidates whose experience, teaching, research, or community service has prepared them to contribute to our commitment to diversity and excellence. The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age or protected veteran status.