About The Position

The Ricardo Otazo Lab at Memorial Sloan Kettering Cancer Center is hiring a postdoctoral research fellow or research associate, depending on prior experience, to develop motion-tolerant pediatric MRI with reduced anesthesia. The work will use non-Cartesian acquisition and deep-learning auto-navigation and reconstruction, including innovations in image acquisition and reconstruction and their application to clinical cases. The successful candidate will join a collaborative, multidisciplinary research environment involving physicists, engineers, computer scientists, and clinicians in Medical Physics and Radiology, with opportunities to contribute to translational research and share research outcomes through conferences and publications. The group develops fast, motion-tolerant MRI techniques, including GRASP, Movienet, and MRSIGMA. The MRI Physics group has access to clinical 1.5T and 3T GE MRI scanners and high-performance computer servers with multiple GPUs for image reconstruction and deep learning. Salary is commensurate with experience and the cost of living in New York City. Subsidized housing near the MSK campus may be available.

Requirements

  • PhD in Physics, Engineering, Computer Science, or a related field.
  • Background in MRI physics.
  • Strong track record of peer-reviewed publications.
  • Ability to work independently and collaboratively.
  • Excellent verbal and written communication skills.

Nice To Haves

  • Expertise in image-reconstruction coding or deep learning.
  • Computer science experience or interest in applying deep learning to MRI.

Responsibilities

  • Develop motion-tolerant pediatric MRI techniques intended to reduce the need for anesthesia.
  • Work on non-Cartesian MRI acquisition and deep-learning auto-navigation and reconstruction.
  • Develop innovations in image acquisition and reconstruction and apply them to clinical cases.
  • Contribute to collaborative, multidisciplinary translational research.

Benefits

  • Subsidized housing close to the MSK campus may be available.
  • Opportunities for professional advancement and to share research outcomes through conferences and publications.
  • Access to advanced imaging and computing resources.

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What This Job Offers

Job Type

Full-time

Career Level

Entry Level

Education Level

Ph.D. or professional degree

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