Biomedical Imaging and Technology PhD training offered at NYU Grossman School of Medicine’s Vilcek Institute of Graduate Biomedical Sciences focuses on the development and application of advanced imaging technologies to improve biomedical research and clinical care.

Students engage in coursework and hands-on research in NYU Langone’s Department of Radiology and its research centers: the Center for Biomedical Imaging and the Center for Advanced Imaging Innovation and Research (CAI2R).

Biomedical Imaging: A Convergence of Science, Engineering, and Medicine

Biomedical imaging is inherently interdisciplinary, bridging physics, chemistry, engineering, mathematics, and computer science with medicine. Research spans hardware and software—including artificial intelligence algorithms—for image acquisition, reconstruction, and analysis. Imaging innovations impact multiple medical specialties—among them: radiology, neurology, cardiology, oncology, and orthopedics—and enable both clinical and preclinical research.

Doctoral trainees learn to think independently and work effectively in collaborative translational teams of scientists, clinicians, and engineers.

State-of-the-Art Biomedical Imaging Technology and Instrumentation

Graduate students have access to state-of-the-art biomedical imaging research facilities that feature clinical and research MRI scanners, a joint PET-MR scanner, an MR-linac, and preclinical micro-MRI and micro-PET/CT systems. Our human MRI scanners cover ultra-low to ultra-high magnetic field strengths and include ultra-strong gradient capabilities.

For machine learning research, students have access to substantial high-performance computing clusters maintained by our imaging research centers.

The department of radiology also runs a comprehensive radiofrequency (RF) engineering laboratory for design and construction of RF coils and a radiochemistry facility for production of PET tracers.

Beyond the radiology department, NYU Langone hosts a comprehensive lineup of scientific cores and shared resources. Students also benefit from the vibrant research environment at NYU Grossman School of Medicine and connection to New York University’s vast research ecosystem.

Curriculum

The curriculum combines coursework that builds a sound understanding of imaging principles with hands-on experience in hardware and software development. Students pursue original research from early on, joining multidisciplinary teams that bridge engineering and medicine.

Electives include:

• Fundamental Concepts of MRI
• Advanced MRI
• MRI Pulse Sequences
• Radiofrequency Coils for MRI
• MRI Acquisition and Reconstruction
• Deep Learning in MRI Reconstruction
• Medical Imaging
• Deep Learning in Medicine
• Visualization of Biological Samples: From In Vivo to Ultrastructure Clinical Anatomy & Organ Systems

See the PhD program course catalog for more details.

To identify affiliated faculty, visit the Vilcek Institute of Graduate Biomedical Sciences find-a-lab tool at osrsites.com/findalab and select “imaging.”

Contact Us

For more information about biomedical imaging and technology PhD training, contact Riccardo Lattanzi, PhD, program director and one of the Vilcek pre-candidacy advisors, at Riccardo.Lattanzi@NYULangone.org or Steven Baete, PhD, graduate advisor and member of the Vilcek Leadership Advisory Council, at Steven.Baete@NYULanone.org.

Faculty

Faculty members are recognized leaders in imaging science, with expertise that spans the full arc of discovery, development, and clinical translation. Many hold major honors from professional societies, including fellowships and medals from the International Society for Magnetic Resonance in Medicine, distinguished memberships in the Academy for Radiology and Biomedical Imaging Research, and fellowships in the American Institute for Medical and Biological Engineering.

In addition to primary affiliations in radiology, many faculty members hold joint appointments across NYU Grossman School of Medicine and NYU Tandon School of Engineering. Faculty members lead NIH-supported investigations and have close collaborations with industry partners such as Siemens Healthineers, a major manufacturer of MRI scanners. Several teach in the PhD in Data Science Medical School Track program at NYU Center for Data Science.

Students

PhD trainees come from a variety of backgrounds, including physics, engineering, biology, medicine, and computer science. Research contributions by doctoral candidates have furthered imaging science and radiology practice with such advances as free-breathing MRI methods, deep learning for image reconstruction, AI for breast cancer diagnosis, and flexible MRI detector technology.

Graduates emerge as independent researchers skilled in imaging science, interdisciplinary collaboration, and methodical approaches to complex research and development problems.