Postdoctoral fellow in deep learning for MR guided treatments (Memorial Sloan Kettering Cancer Center)
Friday 2nd October 2020
Closing date: Nov 30 2020
One opening is available for a postdoctoral fellow with computer vision and machine learning background in the Department of Medical Physics. This is an excellent opportunity for a computational scientist interested in advancing their medical image analysis skills while working on real problems to cure cancer with a multi-disciplinary group of computer scientists, MRI physicists, and clinicians treating cancer patients.
The position is for two years and will focus on the development of deep methods for real-time tumor tracking for motion estimation and compensation for MRI-guided radiation treatments. The developed techniques are expected to be evaluated for real-time MR guided radiation therapy on the new MRI guided linear accelerator.
Ideal candidates must have strong programming background (Python) with knowledge of machine learning applied to computer vision or medical image analysis. Deep learning knowledge and some image registration/segmentation development experience is highly desirable. Candidates are expected to have excellent written and oral communication skills for writing manuscripts and presenting to multi-disciplinary audiences.
Successful execution on the project is expected to result in high impact technical and clinical publications.
Memorial Sloan Kettering Cancer Center is located on the Upper East Side of Manhattan, and is recognized as a world leader in clinical cancer care and research. Interested candidates should send a resume and list of three references via e-mail to:
Harini Veeraraghavan, Ph.D.
Assistant attending computer scientist
Department of Medical Physics
Memorial Sloan Kettering Cancer Center
1275 York Ave.
New York, NY 10065
e-mail: veerarah at mskcc.org
|Organization||Memorial Sloan Kettering Cancer Center|
|Title||Postdoctoral fellow in deep learning for MR guided treatments|