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All applications should be received no later than March 1, 2021.

Fall Deadline

To be fully considered for all assistantships, fellowships, and campus visits, applicants must submit application materials to MUIDSI by January 1, 2021.  Applications received after March 1st will be considered on a case by case basis.


Sufficient background and training to pursue advanced degree in informatics

Preferred GPA

3.3 out of 4.0

Preferred TOEFL Score

577/90 (paper/internet) or a preferred IELTS score of 6.0


Application Materials

  1. Curriculum Vitae
  2. Statement of Purpose, which should include a summary of why you are 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 – At this time, reporting of GRE scores is optional in application to the MU Informatics PhD program.  Regardless, all applicants are encouraged to provide and highlight evidence of excellence in quantitative ability, analytical reasoning, as well as in verbal and written communication of scientific research.
  4. TOEFL score for international applicants, if required.
  5. 3 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. A scanned copy of transcripts from each postsecondary institution

Optional Documents

Applicants are encouraged to submit representative publications in informatics, if available. For more information please visit the Graduate School Website.

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Use the link below to apply through the University of Missouri Graduate School.

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Informatics Doctoral Degree Requirements

Requirements Summary

The following is a brief synopsis of the general degree requirements; please see the MUII Student Handbook for complete details.

  • Students must take courses listed in the core and concentration areas.
  • 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 timeframe.
  • 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.
  • Students must have at least one journal paper published/accepted and at least another one submitted before the scheduled defense from an approved list of informatics related journals.

Financial Support


MUII has a number of fellowships, all of which provide stipends, tuition waivers, and graduate student insurance for 1-4 years.

Currently, two fellowship programs offer either a  2-year support (NIH T32) or a full  4-year support (Life Sciences Fellowship Program). In addition, many faculty members have sizable funding for talented students and may recruit incoming students to their projects.


NIH BD2K T32 Pre-Doctoral Training Program

MUII has an NIH-funded BD2K T32 training program (2016-2021).

The theme of the program is Big Data in One Health.  The program recruits new coming students who are committed to learning Big Data analytics methods/technologies and apply them to translational medicine – from animal model to human health or vice versa.

Each trainee will receive two-year stipends, including tuition and fees with travel and equipment allowance. The MUII graduate committee will nominate candidates to the MU’s BD2K T32 program from the applicant pools. The Advisory Committee of the training program will recommend acceptances based upon their fitness to the theme of the training and potentials to become next generation Big Data informaticians. For even years (2018 and 2020), six new trainees will be recruited and odd years (2019 and 2021), three new trainees will be accepted to the program.

Eligibility: All new applicants of MUII who are US citizen or permanent residents.
Contact: Dr. Chi-Ren Shyu (
For detailed information:

Life Sciences Fellowship Program

The LSC has funding opportunities known as the Life Sciences Fellowship Program (LSF). The LSF is a campus-wide program that supports MU life sciences trainees with four-year stipends, including tuition and fees. The Institute will nominate candidates to the LSF Program from the applicant pools. A selection committee will recommend acceptances based upon undergraduate training, GRE scores, and research interests and career goals.

For detailed information:

Paul K. and Dianne Shumaker Fellowship Program

Thanks to Mr. and Mrs. Paul K. and Dianne Shumaker’s generosity and passion to build a nationally recognized informatics program at MU, MUII and the Department of Computer Science were granted a $1 million endowment in bioinformatics in 2005. This endowment expects to support four 1-year fellowships annually.

Eligibility: All new applicants of MUII
Contact: Mr. Robert Sanders (
Selection Criteria: See PDF

Two Graduate Research Assistant Positions in Computational Biology and Systems Biology

Two graduate research assistant positions are available at Dr. Wan’s Influenza Systems Biology Laboratory, affiliated with the MU Institute for Data Science & Informatics, College of Engineering, School of Medicine, and College of Veterinary Medicine at University of Missouri.

The missions of this lab are to study ecology, evolution, and host-pathogen interaction for emerging and re-emerging infectious diseases, especially influenza viruses, and to develop and apply systems biology based translational approaches to create influenza-less animal population and human communities.

Translational systems biology is an integrated, multi-scale, evidence-based approach that combines laboratory, clinical and computational methods with an explicit goal of developing effective means of control of biological processes for improving human health and rapid clinical application.

The current projects aim to:

  1. Identify and predict emerging risks of influenza viruses for both human and animals (e.g. poultry and swine) using genomics sequences, big data and machine learning approaches;
  2. Develop a universal influenza vaccine, optimize vaccine production and vaccination strategies for disease prevention and quarantine;
  3. Develop machine learning methods to predict vaccine efficacy for each individual based on personal data, a move towards precision medicine;
  4. Understand molecular mechanisms for influenza evolution and influenza virus-host interactions, including host tropisms, pathogenesis, and transmission.

The prospective students are expected with a broad interest in Systems Biology and to work with a multidisciplinary team including both bench and computational scientists. Basic programming skills are required but, and the programming language is not limited to Python, C, Java, or any others. Prior experience with bioinformatics or computational biology is not essential.

Eligibility: All new applicants of MUIDSI
Contact: Mr. Robert Sanders (

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