Assistant/Associate/Full Professors - Computational Precision Health

University of California, Berkeley
San Francisco

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Faculty Jobs
Engineering & Mathematics, Electrical & Computer Engineering, Industrial & Systems Engineering, Science & Technology, Computer Science & Information Technology
Position Type
Tenured & Tenure-Track
Employment Type
Full Time
Institution Type
Four-Year Institution

Assistant/Associate/Full Professors - Computational Precision Health - UC Berkeley Division of Computing, Data Science, and Society; UCSF Bakar Computational Health Sciences Institute

The Division of Computing, Data Science, and Society at the University of California, Berkeley and the Bakar Computational Health Sciences Institute at the University of California, San Francisco are jointly forming a new Graduate Group in Computational Precision Health (CPH) in support of a bold new program in this area, and seek applicants for four open-rank tenured or tenure track FTE (“hard money”) positions. Successful candidates will have a strong track record of applying computational and data sciences to health, broadly defined to include aspects of mental and physical health; population and public health; public policy and economics; and equity and fairness. Newly recruited faculty will hold dual appointments at Berkeley and UCSF, joining a vibrant Graduate Group composed of existing faculty from Departments including Electrical Engineering and Computer Sciences, Statistics, Industrial Engineering and Operations Research and the Schools of Public Health, Business and Information at UC Berkeley; and the Departments of Medicine, Epidemiology & Biostatistics, Neurology, Pediatrics, Physiologic Nursing, Radiation Oncology, and Urology at UCSF.

Computing and data are rapidly transforming how society operates, allowing researchers, health practitioners, and the broader scientific and medical community to address questions that were once intractable by using a combination of large digital data sets, advanced computing, and statistical and computational methods, including machine learning (ML) and inferential methods. The implications for medicine and health are only starting to be realized. The harnessing of new sources of biomedical and clinical data will revolutionize the diagnosis, treatment, and management of disease, extending life spans, improving quality of life, and eradicating some diseases entirely. Realizing this potential requires understanding and improving computational techniques, how health and other data are collected and shared, how both causal inferences and predictions should be made in complex and confounded healthcare situations, how advances in computational precision health need to be integrated with real-world technology and human systems, and how to harness advances in these areas to reduce systemic inequalities.

In response to this need and opportunity, and with the support of a large philanthropic gift, UC Berkeley and UCSF are launching an ambitious cross-campus program in Computational Precision Health. The program builds on the world leadership in computer science and statistics/biostatistics at UC Berkeley, in clinical care and research at UCSF, and in the population and public health sciences at both institutions to support transformational research and doctoral level training at the interface of the computational and health sciences. The vision of the program is to improve the quality, efficiency, and equity of medicine and population health by combining emerging health data with novel analytics, algorithms and advanced computational systems.

Successful applicants are expected to develop a nationally recognized program and collaborate across disciplines to develop research initiatives in the realm of computational precision health. They will be expected to conduct teaching and research at both campuses in the true spirit of the joint program. We seek rising leaders from diverse fields with active research at the intersection of the computational sciences and the health sciences. The specific areas of interest within computational precision health are not restricted, and may include expertise in big data analytics, clinical decision support, electronic health records, health informatics and clinical research informatics, interoperability, algorithms, machine learning, digital health, networking, wearable devices, privacy, and related areas.

Candidates should demonstrate evidence of strong research productivity, potential for securing extramural funding, and a commitment to excellence in teaching and mentoring and to collaborative research. We are particularly interested in scholars with a commitment to and track record of promoting diversity, equity and inclusion in the realms of research, teaching, and/or service. We recognize the intrinsic relationship between diversity and excellence in all our endeavors and embrace open and equitable access to opportunities for learning and development as our obligation and goal. (see for helpful guidelines).

CPH is committed to addressing the family needs of faculty, including dual career couples and single parents. We are also interested in candidates who have had non-traditional career paths or who have taken time off for family reasons, or who have achieved excellence in careers outside academia.

For information about potential relocation to Berkeley, or career needs of accompanying partners and spouses, please visit:

For information about CPH, please visit:

To apply, visit

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