Post-doctoral Researcher

Stanford University
Location: 
Stanford, California
Job Type: 
Full Time
Closing Date: 
Tuesday, October 30, 2018

 

POST-DOCTORAL FELLOW:  MACHINE LEARNING + ADVANCED NEUROIMAGING

 

Center for Advanced Functional Neuroimaging

Lucas Center for Imaging, Radiological Sciences Laboratory, Stanford University

PI’s:  Greg Zaharchuk, Michael Moseley

Our group’s mission is to develop and apply new MRI and PET neuroimaging techniques to better understand the physiology of the normal brain and to improve the diagnosis and management of neurological disease, with the overarching goal to alleviate human suffering.  We are leaders in the field of deep learning and believe that its use in medical imaging will be transformative for the field of radiology.

A Ph.D. in radiology, EE, computer science, physics, biomedical engineering, or a related field is required. The ideal candidate should have first-hand experience in machine learning, particularly the application of deep convolutional neural networks to medical imaging.  Experience with MR physics and/or PET imaging, pulse programming (in particular, GE EPIC) and reconstruction algorithms is a plus. Finally, familiarity with common post-processing software (such as Matlab, Freesurfer, FSL, SPM, etc.) would be helpful.  Candidates should be highly motivated, demonstrate excellent oral and written communication skills, and have the ability to work effectively independently and as part of a multidisciplinary team. The Lucas Center houses several state-of-the-art 3T MRI, one 7T MRI, and a GE PET/MRI.

 

APPLICATION

Interested applicants should send a cover letter describing relevant experience and interests, as well as a curriculum vitae or resume with contact information for three references to: cafn.apply@gmail.com

Stanford University is an equal opportunity employer and is committed to increasing the diversity of its faculty and academic staff. It welcomes nominations of and applications from women and members of minority groups, as well as others who would bring additional dimensions to the University’s research, teaching and clinical missions.