Postdoctoral Opportunity In Healthcare Data Science at the Stanford School of Medicine
Description
A Postdoctoral Scholar in Healthcare Data Science, with a focus on pain science and biomedical informatics is available immediately in the laboratory of Dr. Titilola Falasinnu in the Division of Immunology and Rheumatology (I & R) at Stanford University, Stanford, California, USA.
About us: The Department of Medicine is committed to translating research discoveries into clinical practice to improve health worldwide. The Division of I&R strives to provide outstanding care for patients with autoimmune and rheumatic diseases. I&R’s clinicians and investigators are at the forefront of integrating pioneering, disease-related research into clinical practice, to provide world-class care to our patients.
The Pain Intelligence Lab, co-led by Dr. Titilola Falasinnu, is a multidisciplinary research group at the intersection of pain science, biomedical informatics, and real-world evidence. Situated within the Division of I & R at Stanford University, the lab leverages large-scale electronic health records, administrative claims, patient-reported outcomes, and biomarker data to uncover insights into chronic pain, particularly in autoimmune and rheumatic diseases. Our team is pioneering methods in natural language processing, machine learning, and real-world data analytics to advance pain phenotyping, improve risk prediction, and optimize treatment strategies. The Pain Intelligence Lab offers an intellectually rigorous and collaborative environment for generating impactful, data-driven solutions in pain care.
Location: Stanford, California
Application Deadline: September 31, 2025
Job Type: Full-time, Two years
Job Description
We are seeking a highly motivated Postdoctoral Scholar with strong expertise in healthcare data science, machine learning, and biomedical informatics to join the Pain Intelligence Lab at Stanford University. This is an exciting opportunity to work at the forefront of pain research in a collaborative, interdisciplinary environment that spans rheumatology, pain medicine, behavioral science, and data science.
Primary Responsibilities
· Conduct advanced analyses using large-scale electronic health records, administrative claims data (e.g., Medicaid, Marketscan, Population Data BC), and biorepositories.
· Contribute to studies using natural language processing to extract patient self-management behaviors using data from digital health platforms.
· Support the integration of biomarker and psychosocial data to explore chronic pain risk stratification and treatment responsiveness.
· Lead manuscript preparation and dissemination of findings at national and international conferences.
· Collaborate with investigators across rheumatology, pain medicine, biostatistics, informatics, and behavioral science.
· Optional: mentor junior trainees and contribute to grant writing activities
Required Qualifications:
· Ph.D. in Computer Science, Electrical Engineering, Bioinformatics, Biomedical Engineering, Biostatistics, Epidemiology or a related field.
· Expertise in machine learning, computer vision, and deep learning algorithms.
· Experience with analyzing unstructured and structured scientific and clinical data.
· Proficiency in Python and experience with relevant machine learning and deep learning libraries (e.g., TensorFlow, PyTorch, ScikitLearn).
· Excellent communication skills and the ability to work collaboratively in a multidisciplinary research environment.
· Interest in applying machine learning, deep learning algorithms to improve care for patients with autoimmune and rheumatic diseases.
Required Application Materials: CV, cover letter, and two references.
If you are interested, please send your required application materials to Dr. Falasinnu at tof@stanford.edu.
Location: Stanford,
Job Type: Full-time
Contact
Contact: Titilola Falasinnu
Phone:
Email: tof@stanford.edu
Website: