Diabetes Technology and Precision Diabetes Health Faculty Search

University of California San Francisco

Diabetes Technology and Precision Diabetes Health Faculty Search

  • Institution: University of California San Francisco
  • Location: San Francisco, CA
  • Website: www.ucsf.edu
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Diabetes Technology and Precision Diabetes Health Faculty Search

  • University of California San Francisco | San Francisco, CA
  • Hourglass IconJob Post Expiration: January 12, 2025
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Job TitleDiabetes Technology and Precision Diabetes Health Faculty Search

Position TypeFull Time

Job Category Faculty

Salary Range -

Location San Francisco, CA

Application Deadline -

Contact Information

Contact Name Ronald Ong

Department -

Email ronald.ong@ucsf.edu

Phone -

Job Description

To apply for this job please visit apptrkr.com.

Exciting Faculty Position in Diabetes Technology and Precision Diabetes Health

The UCSF Health Division of Adult Endocrinology and Metabolism, the UCSF Diabetes Center, and the UCSF UC Berkeley Joint Program in Computational Precision Health (CPH) invite applicants for an Open Rank Faculty Position focused on Diabetes Technology and Precision Diabetes Health. This exciting new position aims to attract a current or future leader in computational health research aimed at transforming diabetes care. We particularly encourage applications from scientists or clinician-scientists with expertise in both the computational sciences and cutting-edge health care delivery, focusing on integration of data from wearable devices, including but not limited to continuous glucose monitoring and insulin delivery devices, in optimizing diabetes management. The successful applicant would join the vibrant and growing CPH program, which includes a PhD training program and brings together the world-class expertise and computational resources of both UCSF and UC Berkeley.

The UCSF Diabetes Center is world renowned for its seminal discoveries in types 1 and 2 diabetes as well as obesity. Together with the Division of Endocrinology and Metabolism, the Diabetes Center has a track record of bringing fundamental mechanistic insights in these disease areas directly into clinical care. In addition, UCSF and UCSF Health together offer a robust environment for developing and deploying technologies, including AI/ML models, into operational care delivery.

Depending on best fit, successful candidates will be appointed primarily in either CPH (joint between UCSF and UC Berkeley) or jointly in UCSF’s Division of Endocrinology and Diabetes Center. Candidates would be expected to direct a leading research program in diabetes technology that complements and elevates the strong environments at both campuses. Resources to ensure research success will be provided collaboratively through CPH, the Diabetes Center, and Division of Endocrinology and Metabolism. Candidates with PhD, MD, or both degrees will be considered at the Assistant, Associate, and Full Professor levels.

Qualifications:

MD, PhD, or combined MD/PhD with established expertise in diabetes technology and computational approaches.

Please apply online at https://apptrkr.com/5806495. Applicants’ materials must list current and/or pending qualifications upon submission.

The posted UC salary scales set the minimum pay determined by rank and step at appointment. See [Table 5]( https://www.ucop.edu/academic-personnel-programs/_files/2024-25/oct-2024-scales/t5- summary.pdf). The minimum base salary range for this position is $127,000-$333,700. This position includes membership in the [health sciences compensation plan](https://ucop.edu/academic-personnel
programs/_files/apm/apm-670.pdf) which provides for eligibility for additional compensation.

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.

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