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Open Postdoctoral position, faculty mentor Sherri Rose

Important Info

Faculty Sponsor (Last, First Name): 
Rose, Sherri
Stanford Departments and Centers: 
HRP: Health Services Research
FSI Center for Health Policy
Postdoc Appointment Term: 
Initial appointment is 1 year with renewal after the first year for an additional 1-2 years by mutual agreement.
Appointment Start Date: 
Flexible start date in 2023 or 2024
Group or Departmental Website: 
http://drsherrirose.org
http://healthpolicydatascience.org
How to Submit Application Materials: 

Submit application materials online: https://forms.gle/WWWffe5vUzc1HC448

Does this position pay above the required minimum?: 
Yes. The expected base pay range for this position is listed in Pay Range field. The pay offered to the selected candidate will be determined based on factors including (but not limited to) the qualifications of the selected candidate, budget availability, and internal equity.
Pay Range: 
$107,000-$115,000

Multiple Postdoctoral Research Positions in Health Data Science at Stanford
 
The research group of Dr. Sherri Rose (http://drsherrirose.org/) is seeking multiple postdoctoral scholars in health data science. Postdoctoral scholars will work on grant-funded research projects in health data science that draw on one of two methodological areas: developing (1) microsimulation and discrete-event simulation models or (2) algorithmic bias and fairness methods. The methodology work will support health policy decision-making across various domains, including chronic kidney disease and health spending, among others. Trainees from any computational discipline with demonstrated experience in microsimulation modeling or algorithmic bias methods, including closely related work in nonparametric statistics or statistical learning, are welcome to apply.
 
The culture of Dr. Rose's group is inquisitive, collaborative, kind, and inclusive so that scholars can do their best work. We have high standards for rigor, quality, and ethics and help each other learn to reach these objectives. Every trainee is a human first, and their career goals will be centered and supported. Dr. Rose is Co-Director of the Health Policy Data Science Lab (http://healthpolicydatascience.org), a group of interdisciplinary researchers at Stanford and Harvard, and postdoctoral scholars will be members of the Lab. She is also Co-Director of the Data Science x Decision Science research hub at Stanford.
 
Dr. Rose comes from a low-income background and is committed to increasing justice, equity, diversity and inclusion in the mathematical and health sciences. Postdoctoral scholars will have the opportunity to engage in programming related to these efforts (e.g., conferences, mentoring visiting summer students from underrepresented backgrounds) if they so choose.
 
JOB POSTED: July 26, 2023
CURRENT STATUS: Accepting applications, Rolling review of applications, Rolling first-round virtual interviews, Rolling on campus interviews
Please apply by January 8, 2024 to ensure full consideration of your application.

Required Qualifications: 
  • Ph.D. completed by agreed upon start date
  • Strong programming skills using R or Python
  • [for Microsimulation projects:] Demonstrated experience developing microsimulation or discrete-event simulation models
  • [for Algorithmic bias projects:] Demonstrated experience with algorithmic bias and fairness methods, including closely related work in nonparametric statistics or statistical learning
Required Application Materials: 
  • CV
  • A cover letter describing (1) which postdoctoral role you are applying for (microsimulation or algorithmic bias), (2) your demonstrated experience in the area, (3) your track record leading research projects (need not be published), and (4) your postdoctoral and career goals.
  • A single writing sample not exceeding 30 pages (e.g., published article, thesis chapter, unpublished working paper).
  • Contact information for 2-3 references.

 

Stanford is an equal opportunity employer and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by law.