The MIMI group continuously seeks new people who want to learn and contribute to medical imaging and machine learning research.  Position availability is subject to group size, funding, and synergy of your interests with those of the group.  This information is to help you with choices, both in this group and in others.  Please contact us with any questions!

Note that the application process to Stanford University is done through academic departments, not through individual researchers. Please visit a departmental admission site for specific information regarding admissions. Many of our students are in Electrical Engineering, Bioengineering, and Biomedical Data Science though students in any department are allowed to work in any lab at Stanford.

Learn About This Group: Read the different pages on this site, consider a research rotation if you are a student at Stanford and please contact people in our group with specific questions.

Prerequisites: By definition, research in the MIMI is an interdisciplinary field combining Engineering, Physics, Computer Science and Medicine. Some interest in all of these areas is important for success in this research group. The following should be considered:

Skills: Strong programming skills (languages such as Python, Matlab, C, etc; experience with PyTorch, JAX, Tensorflow, etc; version control and collaborative development with GitHub, etc), written communication skills, oral presentation skills and computer skills (general maintenance, Unix/Linux, debugging!)

Courses: A strong foundation in machine learning will always be beneficial for most research projects in the group. This can be gained through courses such as CS 231N (Convolutional Neural Networks for Visual Recognition), CS 224W (Machine Learning with Graphs), CS 330 (Deep Multi-Task and Meta Learning), CS 224N (Natural Language Processing with Deep Learning), EE 368 (Digital Image Processing).

Different research projects require different skillsets. For example, for MRI projects, the following courses are strongly recommended: EE 261 (Fourier Transforms), EE 369B (Basic MRI), EE 263 (Linear Systems), EE 264 (Digital Filtering). Depending on your research project, the following courses may also be beneficial: CS 229M (Machine Learning Theory), CS 236 (Deep Generative Models), CS 238 (Decision Making Under Uncertainty), CS 246 (Mining Massive Data Sets), CS 329D (Machine Learning Under Distribution Shifts), CS 448I (Computational Imaging and Display).

We also collaborate with several clinicians, which provides excellent learning opportunities to learn clinical research areas.

Much of the information for students applies to more senior positions as well. In general, this group seeks members who have substantial experience in medical imaging and machine learning. You should also be capable of working in a team-oriented environment but also able to independently solve problems.

Try to narrow your interests and find research groups that fit. It is not advised to just look for any group that will fund you. We can help you much more if you tell us your interests, including recommending other groups that may be a good match. Please do not send "form" emails to faculty or researchers - they are usually obvious, and do not serve you well.

Do obtain references from faculty with whom you've worked. If you do project courses, you can get such references. We usually contact references for new members of our group.

This group does not offer medical fellowships - again these are awarded through departments.
If you still have questions, or would like more information, please Contact Us.