Many foreign (and some domestic) applicants are under the impression that one should apply to individual research labs or professors to join graduate programs. However, in most US universities the admission decision is delegated to a department-wide admissions committee, and the only way to be admitted to graduate study is by applying to that process, normally by early December. Only as the last step of admissions (around February or March each year) do we try to match the admitted students' research interests to opportunities within individual research groups, often influenced not only by sharing of common research interests but also availability of RA (Research Assistant) and Fellowship funding and spots opened up by recent graduates.
The MIT Department of Electrical Engineering and Computer Science
(EECS) has a long tradition of encouraging studies in highly
varied fields, and has provided opportunities for nearly fifty
years for doctoral studies in medical informatics. Since the
advent of biomedical informatics as a field in the 1990's, it has
also served as one of the appropriate places to study this field.
Information on applying for admission to EECS may be found at https://www.eecs.mit.edu/academics/graduate-programs/admission-process/,
and the application site is linked from there.
Note that, although EECS expects students to earn a master's
degree on the way to a PhD, there is no terminal master's program,
and candidates interested only in obtaining a master's degree
compete for admission with those planning to study for the PhD.
Harvard/MIT Division of Health Sciences and Technology (HST),
which is part of MIT's Institute
for Medical Engineering and Science, also offers PhD
programs in biomedical engineering/physics (MEMP). Information is
at
https://hst.mit.edu/academic-programs/memp
MIT also hosts a Computational and Systems Biology (CSBi)
doctoral program, described at
https://csbphd.mit.edu
The Institute for Data, Systems
and Society at MIT focuses on large-scale socio-technical
problems in various engineering areas, and has been developing an
interest in the healthcare system as a whole. Their doctoral
program is described at
http://idss.mit.edu/academics/ses_doc/
If you already have an MD or other doctoral degree in a health-related field, we collaborate with a Master's program in biomedical informatics hosted by Harvard Medical School. The program also normally includes association with one of the Boston-area hospitals' informatics laboratories. They also have PhD programs in Bioinformatics and Integrative Genomics and in Artificial Intelligence in Medicine. Information on these programs is at http://informaticstraining.hms.harvard.edu/
A more general discussion of educational opportunities within the MIT CSAIL Clinical Decision Making Group is at http://groups.csail.mit.edu/medg/training/index.html
Although the range of options seems overwhelming, there is
significant overlap among the classes, faculty and labs involved
in many of these programs. Though the admission process may look
disjointed, the educational process is better integrated!
Applicants should be aware that admission to these programs is
highly competitive, so even most fully qualified students are not
admitted simply because we are unable to educate so many good
students. Therefore, it is imperative for anyone seeking a
graduate education in this field to look broadly at many available
programs around the US and the world and to apply to ones that
seem a good match to his or her interests. This maximizes the
chances of admission to some good program, despite the significant
random component of admission committee decisions.
My colleagues in EECS have created a set of hints about the kinds
of evidence of likely success that they are looking for when
reading applications. You may want to look through these here.
I have completed fifty years of teaching at MIT and am approaching retirement. Therefore, I have stopped taking on new doctoral students. Fortunately, I now have many other faculty colleagues with interests that overlap mine, so students interested in working in my research group can find very comparable opportunities in other groups. For example, the EECS web page describing AI for Healthcare and Life Sciences gives an overview of Department activities in this field.