The David Geffen School of Medicine (DGSOM) is searching for tenure-track faculty to join the Department of Computational Medicine. The successful candidate will enjoy a richly collaborative working environment and possible joint appointment with the UCLA Henry Samueli School of Engineering and Applied Sciences (HSSEAS), the UCLA Division of Life Sciences, or the Departments of Biostatistics or Epidemiology in the Fielding School of Public Health (FSPH). We are seeking candidates with strong research programs in the quantitative biomedical sciences, with emphasis on the development and use of novel mathematical models and computational methods. We plan to hire at the Assistant Professor level but will certainly consider exceptional candidates at higher ranks.

The DGSOM and HSSEAS have invested in Computational Medicine to lead the transformation of biomedical sciences by leveraging recent advances in the mathematical, computational, and data sciences. The recently established Institute for Precision Health in the DGSOM provides unique opportunities to build upon successful collaborations between these two schools and encourage new ones. UCLA plans to hire multiple faculty over the next few years with diverse research interests in applications across biology, medicine and public health. Some of the faculty will be hired to support the Department of Computational Medicine’s Biomathematics Graduate Program, a leading program nationally with a long and illustrious tradition, and these faculty will be expected to play an active role in the program. Candidates for these positions will be judged on productivity, creativity, commitment to realistic biological models, mathematical sophistication, and ability to collaborate across disciplinary boundaries. Faculty will also be hired in other interdisciplinary areas of interest including Computational Genomics, Clinical Machine Learning, and Computer Vision applied to Medical Imaging,

Candidates should hold a Ph.D. and/or M.D. or equivalent degree in any relevant discipline, and provide potential for scholarly impact through publications, excellence in teaching, and strong oral and written communication skills. We welcome candidates whose experience in teaching, research, or community service has prepared them to contribute to our commitment to diversity and excellence. Faculty appointment level and salary will be commensurate with the candidate’s experience and qualifications.

Applicants should submit a cover letter, curriculum vitae, list of three references, research statement, teaching statement, and statement of contributions to equity and diversity inclusion via UC Recruit, Please forward any questions to Sriram Sankararaman, Chair of the Computational Medicine Faculty Search Committee.

Cultural North Star: The shared values of the DGSOM are expressed in the Cultural North Star, which was developed by members of our community and affirms our unswerving commitment to doing what’s right, making things better, and being kind. These are the standards to which we hold ourselves, and one another. Please read more about this important DGSOM program at

Questions about the search should be directed towards Sriram Sankararaman (, Chair of the Search Committee, or Eleazar Eskin (, Chair of the Department of Computational Medicine.


Document requirements

  • Curriculum Vitae - Your most recently updated C.V. 

  • Cover Letter

  • Statement of Research

  • Statement of Teaching (Optional)

  • Statement on Contributions to Equity, Diversity, and Inclusion - An EDI Statement describes a faculty candidate’s past, present, and future (planned) contributions to equity, diversity, and inclusion. To learn more about how UCLA thinks about contributions to equity, diversity, and inclusion, please review our Sample Guidance for Candidates and related EDI Statement FAQ document. 

Reference requirements

  • 3-5 letters of reference required

Requesting letters of reference: 3 required, 2 additional optional

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Media Contact: 

Leticia Ortiz | Marketing & Communications | Building a community around data science in biomedicine​