CT Research Scientist Intern

Canon Medical Research USA, Inc. (CMRU) is proud to announce the launch of our 2026 ADVANCE internship program. Students will contribute at the forefront of innovation in medical imaging working alongside leading scientists and engineers as we develop and deliver the latest technology to our parent company Canon Medical Systems Corporation. 

The ADVANCE Program is a structured program with goals and expectations designed to provide students with an opportunity to gain hands-on work experience by participating in significant work projects. Students will take on assignments throughout the term related to CMRU project needs depending on their skills and interests. The goal of these activities is to make important contributions to CMRU programs while at the same time significantly advancing the student’s professional and personal development.

SUMMARY OF POSITION

CMRU is looking for one qualified intern to join our Computed Tomography (CT) research department where the student will participate in exciting projects using latest technology for medical imaging. Students will be mentored by leading experts in the field to gain hands-on experience to develop and validate products, explore the full potential for various clinical applications and features, and contribute to the next generation of spectral CT system. This internship offers a great opportunity to see how your research ideas can come to life and make a difference in countries around the world.

RESPONSIBILITIES

• Develop advanced algorithms to address complex research problems in Computed Tomography.
• Investigate Deep-Learning based method to solve challenging image reconstruction or image processing tasks.
• Design and implement advanced algorithms for next-generation products, such as Photon Counting CT.
• Summarize work in the form of reports and presentations. 

QUALIFICATIONS

• The ideal candidate is a full-time graduate student at an accredited college or university working towards an M.S. or Ph.D. in Biomedical Engineering, Electrical Engineering, Computer Science, Medical Physics, Physics or related field in STEM.
• Students must be eligible to work in the U.S.
• Strong background in image reconstruction, signal and image processing, machine learning, and computer vision.
• Good understanding of X-ray physics and system. Familiar with spectral CT/Photon-counting CT related system design, calibration and image formation chain is a plus.
• Hands on experience in AI/Deep Learning is strongly preferred. Familiar with at least one neural network training framework such as PyTorch or TensorFlow.
• Knowledge of CT clinical applications and anatomy is a plus.
• Strong analytical and programming skills in languages such as C/C++/Python/MATLAB, etc.

Time Commitment

This is a full-time, temporary position that requires a minimum commitment of 12 weeks and 37.5 hours per week, Monday-Friday during regular business hours. This is a hybrid position, which requires in-office work at least 3 days per week.

COMPANY DESCRIPTION

Canon Medical Research USA, Inc. (CMRU) is a multi-modality R&D organization creating next-generation medical imaging systems. It is equipped with cutting-edge instrumentation, prototyping, hardware labs and scientific computing facilities to perform research targeted to pre-clinical and clinical CT, PET, MRI, X-ray and Ultrasound systems. For those who like to develop new technologies and research new ways of using them, Canon is a rewarding place to work, due to its focus on innovation as the lifeblood of new products. 

CMRU is committed to recognizing and appreciating the variety of characteristics that make individuals unique in an atmosphere that promotes work/life balance and celebrates individual and collective achievement. We are especially interested in qualified candidates who can contribute, through their experience, education, research and/or service, to the diversity and excellence of our organization and to the scientific and engineering community at large. We offer a great work environment, including a hybrid work schedule.