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Open Postdoctoral position, faculty mentor Daniel Rubin

Important Info

Faculty Sponsor (Last, First Name): 
Rubin, Daniel
Stanford Departments and Centers: 
Biomedical Data Sciences
Postdoc Appointment Term: 
1 year, potentially renewable
Appointment Start Date: 
Immediately available
How to Submit Application Materials: 

Please submit all application materials in one PDF document to rubin-lab-jobs@lists.stanford.edu

An exciting postdoctoral fellow position is available immediately in the Laboratory of Dr. Daniel Rubin in the Department of Biomedical Data Science, Radiology, and Medicine (Biomedical Informatics Research) at Stanford University. Dr. Rubin’s group focuses on cutting-edge research at the intersection of imaging science and biomedical data science, developing artificial intelligence methods to leverage large amounts of medical data for discovery and to translate these methods into clinical applications that will transform medical care.
 
The postdoctoral fellow will develop natural language processing methods to extract critical findings and other information from radiology reports. These methods will be used to develop a system to alert clinicians about important results that provide timely patient care. The fellow will apply cutting edge text analysis methods, such as transformers in carrying out this work and collaborate with top scientists at Stanford as well as with other institutions nationally. We are seek a motivated, creative, and qualified scientist with excellent written and verbal communication skills.

Required Qualifications: 
  • Post-graduate degree (MD or PhD) and training in Biomedical Informatics, Computer Science, or a related discipline
  • Background and preferably publications in natural language processing
  • Record of distinguished scholarly achievement
Required Application Materials: 
  • Curriculum Vitae
  • Brief statement of research interests and vision (1-2 pages)
  • Three letters of reference

 

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.