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Company Overview

The people of Memorial Sloan Kettering Cancer Center (MSK) are united by a singular mission: ending cancer for life. Our specialized care teams provide personalized, compassionate, expert care to patients of all ages. Informed by basic research done at our Sloan Kettering Institute, scientists across MSK collaborate to conduct innovative translational and clinical research that is driving a revolution in our understanding of cancer as a disease and improving the ability to prevent, diagnose, and treat it. MSK is dedicated to training the next generation of scientists and clinicians, who go on to pursue our mission at MSK and around the globe.

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Job Description

Exciting opportunity at MSK: Join our team as an MRI Research Scientist, Quantitative MRI and Deep Learning! We're looking for a dynamic professional to work in a multidisciplinary group including physicists, engineers, computer scientists and clinicians in the departments of Medical Physics and Radiology.

Role Overview:

• Develop quantitative MRI methods broadly applied to cancer diagnosis and response assessment.
• Collaborate with MSK Radiologists on developing a combination of pulse sequence programming, optimization, and new deep learning approaches as well as application of developed technology to clinical cancer cases.
• Develop and code software programs, algorithms, and automated processes to implement new MRI technology into clinical scanners.
• Interpret and communicate insights and findings from analysis and experiments to product, service, and business managers.
• Participate in running imaging experiments.
• Debug and troubleshoot software to resolve defects.
• Build effective working relationships with development and cross-functional team members.
• Author and/or contribute to technical design documentation, release notes, bug fix documentation.
• Perform and design testing protocols to ensure that the product is fully tested.

Key Qualifications:

• Master's degree in Electrical Engineering, Biomedical Engineering, Computer Science, or a related area.
• Background in MRI physics and deep learning.

Core Skills:

• Computer programming expertise in Matlab and Python, and C++ (required)
• Outstanding attention to detail and strong analytical and interpersonal skills.
• Planning and prioritizing work to meet commitments aligned with organizational goals.
• Critical thinking and problem-solving to ensure unforeseen issues are handled appropriately and resolved in a timely fashion.
• Excellent communication skills and the ability to interact across all levels in a confident, professional manner.
• Enthusiasm and dedication to MSK's vision, mission and values.

Additional Information :

• Location: Joy Building, 321 E 61st Street, NYC
• Schedule: Hybrid, able to come on site 2-3 days a week, if needed.

Pay Range: $120,200 - $192,300

Helpful Links :

• MSK Compensation Philosophy
• Review our great benefits offerings

Learn more about the Cohen Lab : The Cohen lab has substantial research time at clinical MRI scanners in the Department of Radiology, including state-of-the art 1.5T and 3T GE scanners and a 3T PET-MR GE scanner. The group also has access to high performance computer servers with multiple GPUs for image reconstruction and analysis tasks. Deep learning methods have recently experienced tremendous growth in popularity due to their effectiveness and ease of use. In this project, we aim to develop deep learning reconstruction and quantification methods to accelerate the MRI reconstruction and further extract clinically useful data from the MR acquisition.

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Closing

MSK is an equal opportunity and affirmative action employer committed to diversity and inclusion in all aspects of recruiting and employment. All qualified individuals are encouraged to apply and will receive consideration without regard to race, color, gender, gender identity or expression, sexual orientation, national origin, age, religion, creed, disability, veteran status or any other factor which cannot lawfully be used as a basis for an employment decision.

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