Dr. Amelia Sattler

Assistant Professor

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Biography

Amelia Sattler is a Clinical Associate Professor in the Department of Medicine at Stanford University, specializing in Primary Care and Population Health. She completed her undergraduate degree in psychology at the University of Puget Sound and underwent medical training at Mayo Medical School. With a strong commitment to enhancing patient care, Amelia focuses on health care innovation, clinical quality improvement, and adolescent mental health. She has held various leadership roles, including the Associate Program Director for the Stanford Healthcare AI Applied Research Team, and is actively involved in integrating behavioral health into primary care through collaborative models. Her clinical interests encompass adolescent medicine, mental health, and population health innovation. Amelia values the importance of education and mentorship, serving as the Director of the Continuity Care Clerkship and playing a pivotal role in the O’Connor-Stanford Leaders Education Residency Pathway. Outside of her professional endeavors, she enjoys spending quality time with her family and engaging in outdoor activities.

Research Interests

Experience

Clinical Associate Professor

2024-01-01 — Present

Stanford University • Stanford, California

Teaching and providing clinical oversight in the Department of Medicine.

Primary Care Program Director

2022-01-01 — Present

Stanford Healthcare • Stanford, California

Leading the integration of behavioral health within primary care.

Courses

FAMMED 370 FAMMED 199

Requirements for Stanford University

Doctorate Program
Requirements
GPA Requirement
Required:3.5
TOEFL
Listening
Required:26
Reading
Required:26
Writing
Required:26
Speaking
Required:26
Total
Required:100
GRE General
Verbal
Required:160
Quantitative
Required:165
Analytical Writing
Required:4.5
Overall
Required:4.5
Prerequisites
Bachelor degree from an accredited institution Strong background in mathematics and programming
Application Checklist
  • Statement of Purpose
  • Three letters of recommendation
  • Official transcripts
  • Resume/CV
Specialization Notes

The Computer Science department emphasizes research potential. GRE General is currently optional but recommended for some tracks.