|Title: Postdoctoral scholar in medical image analysis||Posted: November 25, 2015|
|Company/Institution: Stanford University|
|Location: Stanford, CA|
|Department: Radiation Oncology|
Description: We are looking for a highly motivated postdoctoral research fellow at Stanford University School of Medicine, within the Department of Radiation Oncology. We are developing quantitative imaging biomarkers for personalized cancer prognosis and prediction of therapy response based on multi-modality imaging such as PET, CT, and/or MRI. We analyze and integrate imaging data with clinical and/or genomic information, with the goal of transforming clinical care through translational research. There are several ongoing projects on multiple cancers, including brain, breast, lung, head/neck, and pancreatic cancers. We work closely with radiologists and oncologists. For more information about our research, see http://med.stanford.edu/lilab
Candidates with a Ph.D. in biomedical engineering, electrical engineering, computer science, physics, or a related area are invited to apply. Prior experience with medical imaging (in particular, image processing and analysis) is required. Familiarity with bioinformatics, mathematical or statistical modeling, machine learning and data mining is highly desired. Strong programming skills are required. We are seeking a highly motivated individual with well-developed communication skills and the desire and talent to tackle challenging technical problems in medicine.
I am dedicated to mentoring and educating the future leaders in biomedical research. Some major awards won by postdocs in the lab include: the ASTRO Resident Clinical/Basic Science Research Award (2014), and the ASTRO Basic/Translational Science Abstract Award (2015). ASTRO is the world’s largest professional society for radiation oncologists.
Application Instructions: Interested applicants should send Curriculum Vitae with publications and research experience/skills, and the names and contact information of 3 referees to:
Ruijiang Li, PhD, DABR
Department of Radiation Oncology