PhD in Informatics with Emphasis in Health Informatics

Degree Requirements

The following is a brief synopsis of the general degree requirements; please see the Informatics Institute web site:

  • Students must take required and area courses.
  • Students must pass a qualifying examination.
  • Students must present at least one institutional seminar annually.
  • Students are required to complete a comprehensive exam, which includes written and oral elements, within a specified time frame.
  • Students must pass a comprehensive examination at least 7 months before their scheduled defense.
  • Students must submit and defend a dissertation describing the results of successful and original research in one of the branches of informatics.
  • To show research progress, students are expected to be working toward presenting at conferences and publishing in peer-reviewed journals based on their informatics research.

Coursework Requirements

All students must have at least 72 credit hours at the graduate level, of which 15 credits must be at the 8000-level not including research, problems, lab rotations, or seminar.  Transferring credits will be at the recommendation of the student's doctoral committee and the approval of the MUII Curriculum Committee.

REQUIRED COURSES - HEALTH INFORMATICS EMPHASIS AREA
DATA_SCI 7010Introduction to Data Science and Analytics3
INFOINST 7430Introduction to Health Informatics3
REQUIRED METHODS COURSES (9 Credit Minimum)
INFOINST 8810Research Methods in Informatics3
STAT 7510Applied Statistical Models I3
Students must choose one additional 3-credit methods course with doctoral committee approval.
LAB ROTATIONS AND SEMINAR
INFOINST 8087Seminar in Informatics (Must be enrolled each semester)0.5-1
INFOINST 8088Lab Rotations in Informatics2
RESEARCH
INFOINST 8090Dissertation (pre-candidacy) Research in Informatics1-99
INFOINST 9090Dissertation (post-candidacy) Research in Informatics1-99
AREA COURSE ELECTIVES (15 credits)
AN_SCI 7001Topics in Animal Science1-4
CMP_SC 7380Database Management Systems I3
CMP_SC 7740Interdisciplinary Introduction to Natural Language Processing3
CMP_SC 8370Data Mining and Knowledge Discovery3
CMP_SC 8630Data Visualization3
ECE 7270Computer Architecture4
ECE 7590Computational Neuroscience4
ECE 8320Nonlinear Systems3
ECE 8570Neural Dynamics and Communication3
ECE 8580Machine Learning in Neuroscience3
GEOG 7620Biogeography: Global Patterns of Life3
GEOG 7710Spatial Analysis in Geography3
GEOG 7810Landscape Ecology and GIS Analysis I3
GEOG 7840Geographic Information Systems I3
GEOG 7860Advanced Remote Sensing3
GEOG 7940Advanced Geographic Information Systems (GIS II)3
GEOG 8840 Seminar: Applied Remote Sensing
GEOG 8902Topics in Geography-Biological/Physical/Mathematical1-3
HMI 7410Introduction to the US Health Care System3
HMI 8435Information Security, Evaluation and Policy3
HMI 8437Data Warehousing and Data/Text Mining for Health Care3
HMI 8441Biomedical and Health Vocabularies and Ontologies3
HMI 8443Enterprise Information and Solutions Architecture for Strategic Healthcare Operations3
HMI 8460Administration of Health Care Organizations3
HMI 8461Managing Human Resources in Health Care Organizations3
HMI 8478Knowledge Management in Health Care3
HMI 8524Health Economics3
HMI 8565Health Care Ethics3
HMI 8571Decision Support in Health Care Systems3
HMI 8573Decision Making for Health Care Organizations3
HMI 8610Consumer Health Informatics3
IMSE 8810Human Factors3
INFOINST 8005Applications of Bioinformatics Tools in Biological Research3
INFOINST 8085Problems in Informatics1-6
INFOINST 8150Integrative Methods in Bioinformatics3
INFOINST 8190Computational Systems Biology3
INFOINST 8310Computational Genomics3
INFOINST 8870Knowledge Representation in Biology and Medicine3
IS_LT 9410Seminar in Information Science and Learning Technology1-3
NURSE 9460Theories and Interventions in Health Behavior Science 3
PTH_AS 7450Precision Medicine Informatics3

Qualifying Exam Process

Students are expected to take the qualifying exam by the end of their third semester in the program.  The exam will be based on their previous coursework, lab rotation experience, and one-page research statement.  For more information on qualifying exam procedures, please see the MUII student handbook.

Comprehensive Exam Process

The comprehensive exam consists of two parts - the written portion, comprised of an R01 research proposal, and the oral exam.  For more information on the comprehensive exam process, please see the MUII student handbook.

Dissertation Defense Process

The doctoral dissertation defense must be scheduled no sooner than seven months after successful completion of the comprehensive exam. The dissertation must be written on an informatics subject approved by the candidate's doctoral program committee, must embody the results of original and significant investigation, and must be the candidate's own work.  Please refer to the MUII student handbook for additional information.

Admission Contact Information

MUII Staff (mailto: muiiadmissions@missouri.edu)
241 Naka Hall
Columbia, MO 65211-2060
Phone: 573-882-9007
FAX: 573-884-8709
Informatics Institute (MUII) website: http://muii.missouri.edu/

Admission Criteria

Fall deadline: The deadline for Fall admission is March 1. However, to be considered for departmental and Graduate School fellowships and assistantships, applications should be submitted by January 15.

  • Preferred GPA: 3.3 out of 4.0
  • Preferred GRE scores*:
When did you take the GRE? Verbal + Quantitative Analytical
Prior to August 1, 2011 1200 3.5-4.0
On or After August 1, 2011 309 3.5-4.0
  • Preferred TOEFL or IELTS scores
Internet-based test (iBT) Paper-based test (PBT)
90 577
Item Score
Minimum IELTS Score 6.0

All Required Documents

Students are required to send ALL required application materials through the Office of Graduate Schools on-line application system. To begin your application, please see the ApplyYourself website.

  1. Curriculum Vitae
  2. Statement of Purpose, which should include a summary of why the applicant is interested in pursuing an advanced informatics degree, a brief description of your previous research experiences, the specific area of informatics you are interested in pursuing, and your future career goals and plans in the informatics field.
  3. GRE/GMAT scores.  Use institution code 6875.  The departmental code is not required.
  4. TOEFL/ELTS scores for international applicants, if required. 
  5. Three letters of recommendation from faculty or supervisors who can evaluate the applicant’s credentials and potential to become successful in the area of informatics.
  6. Scanned copies of transcripts from each college and university attended.  If accepted, applicants will be required to have official copies of their transcripts sent directly from the institution to the Graduate School.

Optional Documents

Applicants are encouraged to submit representative publications in informatics, if available.

REQUIRED COURSES - HEALTH INFORMATICS EMPHASIS AREA
DATA_SCI 7010Introduction to Data Science and Analytics3
INFOINST 7430Introduction to Health Informatics3
REQUIRED METHODS COURSES (9 Credit Minimum)
INFOINST 8810Research Methods in Informatics3
STAT 7510Applied Statistical Models I3
Students must choose one additional 3-credit methods course with doctoral committee approval.
LAB ROTATIONS AND SEMINAR
INFOINST 8087Seminar in Informatics (Must be enrolled each semester)0.5-1
INFOINST 8088Lab Rotations in Informatics2
RESEARCH
INFOINST 8090Dissertation (pre-candidacy) Research in Informatics1-99
INFOINST 9090Dissertation (post-candidacy) Research in Informatics1-99

Exceptional Funding Opportunities - Biomedical Big Data Science Pre-doctoral Training

Funded by NIH T32 (2016-2021)

MU Informatics Institute (MUII) is recruiting SIX top-notch trainees to pursue PhD degree in Informatics through an interdisciplinary training team. Students from basic sciences, life sciences, medicine, and computing disciplines are welcome to apply. Our unique training includes: (1) personalized training modules from core courses of the MS degree in Data Science and Analytics program, Big Data courses from Computer Science, and biomedical informatics courses from MUII, which will expose trainees to the basic concepts, ethics, and working knowledge in Big Data Science; (2) a problem-based learning curriculum in pre-doctoral-level Big Data-related courses, such as Mining Massive Data Sets for Biomedical Applications, designed to foster a team science approach to problem-solving; (3) a student-driven journal club/seminar series, in which students are offered opportunities to present research, pose questions, and receive feedback from peers and mentors. Our interdisciplinary components include (1) required tri-lab rotations to introduce students to animal/veterinary medical research, human medical research, computing/statistical methodologies, and health communications; (2) development of rigorous and reproducible open-source Big Data analytics tools, which will be assessed by the One Health research community after arduous testing; and (3) creation of an Individual Development Plan based on each trainee's background and career goal prior to joining the program. These positions are open to permanent residents and US citizens only. Women and minority students are encouraged to apply.

Please contact the project director Dr. Chi-Ren Shyu at ShyuC@missouri.edu for inquiries.