Important Info
Submit all required application materials to klschreiber@stanford.edu
Review of applications will begin 11/1/2026 and continue until the position is filled.
The laboratory of Dr. Kristin L. Schreiber invites applications for a postdoctoral fellowship investigating individual differences in pain and recovery after surgery. We seek a researcher with a background in neuroscience, psychology, or a related discipline, complemented by strong skills in statistics, computational modeling, or data science.
This position offers the opportunity to connect quantitative research with clinically meaningful questions: Who develops persistent pain after surgery? What mechanisms contribute to that risk? How can we identify patients most likely to benefit from preventive interventions, and keep them from developing a chronic pain condition?
Research program
Our translational research program examines how psychological, behavioral, sensory, inflammatory, and clinical factors interact during the transition from acute to chronic postsurgical pain. Supported by independent NIH and institutional funding, our studies combine detailed preoperative assessments, quantitative sensory testing, perioperative inflammatory biomarkers, daily postoperative symptom diaries, and long-term follow-up.
Working within a collaborative network of physician scientists and research mentors, the fellow will help develop an analytical program that advances mechanistic understanding and personalized perioperative care. Specific projects will reflect the fellow’s expertise and interests, with opportunities to:
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Model pain and recovery trajectories. Analyze longitudinal changes in pain, function, psychological symptoms, and analgesic use to identify predictors of recovery and persistent pain.
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Identify pain vulnerability phenotypes. Apply and evaluate clustering, latent profile, and trajectory-based approaches to characterize patient subgroups across surgical populations.
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Develop and validate prediction models. Integrate patient-reported, sensory, biological, and clinical measures; evaluate generalizability across independent cohorts; and identify concise assessments suitable for clinical use.
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Investigate inflammatory mechanisms. Examine relationships among preoperative psychosocial factors, perioperative inflammatory responses, and subsequent pain, including potential mediating pathways.
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Understand differences in treatment benefit. Investigate whether patient characteristics modify responses to regional anesthesia, acute pain services, and other perioperative interventions.
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Translate research into clinical pathways. Explore how detailed phenotyping can inform risk assessment using electronic health records and support actionable decisions within perioperative workflows.
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Develop and test preventive analgesic strategies. Investigate pharmacologic, procedural, and behavioral interventions to improve surgical recovery. Areas of interest include prehabilitation targeting cognitive, physical, nutritional, and sleep domains, as well as interventions to optimize immune and inflammatory responses to surgical injury.
Responsibilities
The fellow will develop research questions, design and conduct analyses, lead manuscripts, and present findings at scientific meetings. They will collaborate with clinical investigators and quantitative researchers, build reproducible analytical workflows, and contribute to new studies and funding proposals.
The role offers substantial intellectual ownership alongside close collaboration with investigators collecting and interpreting the underlying clinical and phenotypic data.
Mentorship and research environment
Dr. Schreiber is a physician scientist, Professor of Anesthesiology, and Division Chief of Regional Anesthesia at Stanford University. Her training spans neuroscience and pain pharmacology, regional anesthesia, biostatistics, and clinical research. Her research connects direct perioperative patient care with the investigation of pain mechanisms and personalized prevention. She has successfully mentored a range of undergrads, medical students, residents, postdoctoral fellows, and junior faculty across a wide range of specialties and training backgrounds.
The fellow will be based in the Schreiber Lab at Stanford University in Stanford, California, with exposure to perioperative care, patient experiences, and the collection of detailed clinical research data. The anticipated mentorship structure includes collaborators with expertise in data science (Aghaeepour) and immunology (Gaudilliere), providing complementary methodological and scientific guidance.
Mentorship will support rigorous research, publication, fellowship and grant development, and an independent scientific direction aligned with the fellow’s career goals.
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A PhD or equivalent doctoral degree in neuroscience, psychology, quantitative psychology, biostatistics, data science, computational biology, or a related field by the appointment start date.
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Demonstrated experience applying statistical or computational methods to research data.
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Proficiency in SPSS, R, Python, or comparable analytical software.
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Strong scientific writing, communication, and collaborative skills.
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Interest in pain research, the biological and psychological bases of individual differences in pain physiology, and implementation research.
Preferred qualifications:
Experience in one or more of the following areas:
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Development and implementation of behavioral interventions.
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Participant recruitment and conduct of observational or interventional studies.
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Statistical analysis and data science methods, including longitudinal and multilevel modeling, predictive modeling, regression, clustering, latent variable methods, trajectory analysis, mediation, moderation, causal inference, model validation, or missing-data methods.
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Integration of patient-reported outcomes, biomarkers, or electronic health record data.
Applicants do not need expertise in every listed method. Prior experience in pain research is welcome but not required.
Please provide:
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A cover letter describing your research interests, quantitative experience, and fit with the position.
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A curriculum vitae.
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One representative publication or research writing sample.
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Names and contact information for three references.