Epidemiology Faculty: Predictive Analytics & Teaching

UCSF Health, AG; San Francisco (CA); On-site; USD 122,000 - 190,000; Full time

Job summary

University of California, San Francisco (UCSF) invites applications for a Faculty Position as Epidemiology Assistant or Associate Professor in the Department of Epidemiology and Biostatistics in San Francisco, CA.

The successful candidate will lead an independent research program, teach methods in epidemiologic research, mentor trainees, and contribute to service while advancing predictive analytics and informatics in healthcare.

Qualifications

• Doctorate-level professional degree in medicine, pharmacy, or nursing (or equivalent clinical experience).
• Graduate-level training in epidemiology, public health, informatics or related field.
• Expertise with methods of contemporary predictive analytics in clinical decision-making (ML included).
• Strong interest and experience teaching predictive analytics to diverse audiences.
• History of extramural funding for Associate level applicants.
• Experience with EMR-based informatics and/or research; familiarity with causal inference.

Responsibilities

• Lead an independent, extramurally funded research program.
• Participate in formal instruction to professional and graduate students in research methods.
• Provide project-specific and career mentoring to trainees.
• Contribute to departmental and university service.

Skills

Predictive analytics methods

Teaching experience

EMR informatics

Causal inference

Education

Doctorate-level professional degree in medicine, pharmacy, or nursing

Graduate-level training in epidemiology, public health, informatics or related field

Job description

University of California, San Francisco (UCSF) invites applications for a Faculty Position as Epidemiology Assistant or Associate Professor in the Department of Epidemiology and Biostatistics in San Francisco, CA.

The successful candidate will lead an independent research program, teach methods in epidemiologic research, mentor trainees, and contribute to service while advancing predictive analytics and informatics in healthcare.