RESEARCH & RESIDENCY POSITION IN MEDICAL PHYSICS, Department of Medical Physics

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Summary:

Summary here.

Details

Posted: 24-Jan-26

Location: New York, New York

Type: Full-time

Categories:

Staff/Administrative

Internal Number: 95499

About Us:

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.

Role Overview

We have an opening for a hybrid research and medical physics residency position in the Department of Medical Physics, with a flexible start date for the right candidate. This is a hybrid residency program in which a two-year grant-funded research project is followed by a two-year clinical residency in either therapeutic or diagnostic medical physics. Those who enter the 4-year program without CAMPEP credentials must apply to enroll in a concurrent CAMPEP Certificate program. If you are accepted into the Certificate program, the department will provide full tuition reimbursement. You will be required to complete the Certificate program during the first two years of the program before entering clinical training.

The two-year research project will be focused on deep learning based dose accumulation for pancreas patients undergoing MR-guided radiotherapy under the direction of Drs. Neelam Tyagi and Harini Veeraraghavan in collaboration with a dynamic team of clinicians and research scientists. The candidate is responsible for developing and investigating longitudinal and multi-modal AI models for deformable image registration and dose accumulation, conducting large-scale retrospective analysis, and preparing manuscripts for publication. Additionally, the candidate will have the opportunity to contribute to other research projects undertaken by the team as appropriate.

Key Requirements

• Doctorate in physics, medical physics, computer science, biomedical/electrical engineering, or similar scientific discipline. * Interest in and commitment to high quality patient care.
• Experience in medical imaging and machine learning for data extraction. * Experience in biostatistical analysis preferred.

Application Instructions

• Submit a single, merged PDF that includes a letter of intent, CV, undergraduate and graduate transcripts, and 3 letters of recommendation. Alternatively, letters of recommendation may be sent separately to estimej@mskcc.org.

Core Skills

• Programming skills with Python, Pytorch, C++, and MATLAB * Expertise in computer vision/medical image analysis and machine/deep learning
• Additional requirements may be necessary for admission into a concurrent certificate program

Contact Information

• If you have any questions about this job opportunity, please contact: Jeanne Romulus, BS Medical Physics, Residency Coordinator Department of Medical Physics estimej@mskcc.org

Pay Range: $72,000- $78,676

Additional Info The Department of Medical Physics consists of over eighty faculty physicists and computer scientists plus support staff working on various physical problems related to diagnosis and therapy for cancer. MSKCC has an extensive, cutting-edge program in all aspects of radiation oncology physics that seeks to improve the clinical effectiveness of radiation therapy in partnership with radiation oncologists, radiologists, and other medical professionals. Many new programs in radiation therapy research and development are ongoing, including the development of realtime motion adaptation during treatment on the MR-linac and conventional linac platforms, the development and clinical use of predictive models using machine learning/AI for treatment planning, improved treatment planning optimization algorithms, integration of MR and PET imaging into radiotherapy decision making and treatment planning, 4D imaging and motion management, the use of Deep Learning and AI for image analysis and tissue segmentation, and the development of informatics-based adaptive radiotherapy processes (www.mskcc.org/departments/medical-physics). Medical physics resources include thirty linear accelerators, one combined treatment room-MRI-Linac system, six HDR units, CT, PET/CT, MRI simulators, and state-of-the-art inter-and intra-fractional imaging and motion management capabilities. We can access a high-performance computer cluster with the most advanced GPU resources. We also partner with the New York Proton Center, which houses one cyclotron, three rotational gantry treatment rooms, one fixed beam treatment room, one research beam room, PET/CT, two CTs, two MRIs, and related clinical support space.

Details of the residency program (including admissions requirements) can be found at https://www.mskcc.org/hcp-education-training/residencies/residency-therapeuticmedical-physics and https://www.mskcc.org/hcp-educationtraining/residencies/medical-imaging-physics-residency

The successful candidate will be compensated according to the MSKCC standard rates based on experience. Specific information on employee benefits offered may be found at https://careers.mskcc.org/about-msk/benefits/

Pay Range: $0.00 - $10,000,000.00

FSLA Status: Exempt

Closing:

At MSK, we believe in fair, competitive pay that reflects your job, experience, and skills.

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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