Postdoc: Motion-Tolerant Pediatric MRI & AI Reconstruction

Memorial Sloan Kettering Cancer Center; New York (NY); Sur place; USD 72 000 - 94 000; Plein temps

Résumé du poste

Memorial Sloan Kettering Cancer Center (MSK) is seeking a postdoctoral research fellow or research associate for the Otazo Lab to advance motion-tolerant pediatric MRI with reduced anesthesia using non-Cartesian acquisition and deep learning auto-navigation.

You will work with physicists, engineers, computer scientists and clinicians in Medical Physics and Radiology, developing novel imaging techniques and applying them to clinical cases with access to advanced imaging resources and

Qualifications

• PhD in Physics, Engineering or Computer Science, or related field.
• Background on MRI Physics.
• Expertise in image reconstruction coding, or deep learning is a plus.
• A strong track record of peer‑reviewed publications.
• Highly motivated with the ability to work both independently and collaboratively.
• We also invite computer scientists interested in applying deep learning to MRI.
• Excellent verbal and written communication skills are required.

Responsabilités

• Develop motion-tolerant pediatric MRI with reduced anesthesia using non-Cartesian acquisition and deep learning auto-navigation and reconstruction.
• Innovate in image acquisition and reconstruction; apply to clinical cases.
• Collaborate with a multidisciplinary team of physicists, engineers, computer scientists and clinicians in Medical Physics and Radiology.
• Contribute to translational research and disseminate findings through conferences and publications.

Connaissances

MRI Physics

Image reconstruction

Deep learning

Publications

Independent work

Collaboration

Formation

PhD in Physics, Engineering or Computer Science

Description du poste

Memorial Sloan Kettering Cancer Center (MSK) is seeking a postdoctoral research fellow or research associate for the Otazo Lab to advance motion-tolerant pediatric MRI with reduced anesthesia using non-Cartesian acquisition and deep learning auto-navigation.

You will work with physicists, engineers, computer scientists and clinicians in Medical Physics and Radiology, developing novel imaging techniques and applying them to clinical cases with access to advanced imaging resources and