Advanced control of radiofrequency hardware for MRI

Magnetic resonance imaging (MRI) allows us to image the human body non-invasively, free of radiation and with extraordinary tissue contrast. The image is generated by the interaction of the hydrogen nuclear spin with a set of external magnetic fields. Each of these fields are generated by a different layer of hardware with unique specifications. 

The MRI Engineering Team (MRIEngT) is dedicated to the development of state-of-the-art radiofrequency (RF) hardware and its control to advance human brain MRI. The team is part of the In Vivo NMR Center, located in the NIH Clinical Center at Bethesda main campus, a multi-institutional and multi-disciplinary facility with a wide range of human and animal MRI scanners (from 0.064 T to 14 T). The MRIEngT is developing new RF transmit and receive technologies for the next generation of MRI scanners. 

The prospective summer student will work on a project related to the control and monitoring of one of these technologies using a combination of prior-knowledge and machine learning (ML) based models. A background on ML/AI algorithms, systems and control, and some hands-on experience on the electronics workbench is required. The student will have the support of team members to get familiarized with the hardware and measurements. While contributing to the project, the student will have the opportunity to learn basics on MRI systems, RF electronics and instrumentation.