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Open Postdoctoral position, faculty mentor Elsie Ross

Important Info

Faculty Sponsor (Last, First Name): 
Ross, Elsie
Department Name: 
Cardiovascular Institute
Postdoc Appointment Term: 
8/01/2019-7/31/2020
Appointment Start Date: 
Flexible
How to Submit Application Materials: 

Postdoctoral Position in Clinical Research for Cardiovascular Diseases at Stanford University School of Medicine
Join an exciting translational data science and technology lab at the world class Stanford University School of Medicine!
The Ross Lab in the Division of Biomedical Informatics Research and Division of Vascular Surgery at Stanford University School of Medicine is looking to recruit an outstanding postdoctoral scholar with experience in genetic epidemiology and an interest in developing precision health care tools to enable next generation health care delivery. This position provides the opportunity to perform a deep dive into the clinical area of cardiovascular diseases, and utilize large scale data in order to better understand the drivers of disease development and inform personalized disease risk modeling and treatment recommendations.
 
Atherosclerotic cardiovascular disease is one of the leading killers of adults in the Western world and leads to billions of dollars in annual health care expenditures. The Ross lab has a special focus on an advanced form of cardiovascular disease known as peripheral artery disease, and uses big data and advanced analytical tools to develop important clinical insights and translate these insights into actual patient care.
 
The Ross lab is located on the Stanford University School of Medicine main campus, which enables multidisciplinary collaborations with teams and world leaders in the fields of epidemiology, biomedical informatics, clinical research and computer science. Opportunities for scientific and career growth are abundant.
 
Potential projects include (but are not limited to):
• Using big data to quantify the contribution of clinical, social, environmental and genetic factors to the development of vascular disease 
• Evaluating how personalized risk factors (e.g. genomics, proteomics, sociodemographic factors) affect treatment response and long-term outcomes
• Developing and applying genetic and clinical risk models for real-time personalized disease risk prediction
 
This position is funded internally for a year with the possibility of an additional year of funding. Possibility for part-time effort available. 

Required Qualifications: 
  1. A MD and/or PhD in biostatistics, bioinformatics, computational biology, or genetic epidemiology and experience working with large genetic data sets
  2. Proficiency with R, Python, STATA and/or SAS
  3. A record of peer reviewed publications with excellent written scientific English skills 
  4. Enthusiasm for learning new skills
Required Application Materials: 
  1. A complete CV with a list of publications
  2. A cover letter describing your research interests and qualifications
  3. Contact information of 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.