To be fully considered for all assistantships, fellowships, and campus visits, applicants must submit application materials to MUIDSI by January 1, 2023. Applications received after March 1st will be considered on a case by case basis.
Sufficient background and training to pursue advanced degree in informatics
3.3 out of 4.0
Preferred TOEFL Score
577/90 (paper/internet) or a preferred IELTS score of 6.0
- Curriculum Vitae
- 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
- GRE/GMAT scores – At this time, reporting of GRE scores is optional in application to the MU Institute for Data Science and 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.
- TOEFL score for international applicants, if required.
- 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
- A scanned copy of transcripts from each postsecondary institution
Applicants are encouraged to submit representative publications in informatics, if available. For more information please visit the Graduate School Website.Visit Grad Studies Website
Use the link below to apply through the University of Missouri Graduate School.
Informatics Doctoral Degree Requirements
The following is a brief synopsis of the general degree requirements; please see the MUIDSI 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.
MUIDSI 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.
Graduate Research Opportunities in Water Studies and Sustainability
The Hydrology Research Group led by Dr. Noel Aloysius at the University of Missouri is seeking 2-4 motivated students to pursue PhD studies in water and natural resources management. Students can enroll in one of the following units:
- Biomedical, Biological and Chemical Engineering (https://engineering.missouri.edu/academics/bbce/)
- School of Natural Resources (https://snr.missouri.edu/)
- Institute for Data Science and Informatics (https://muidsi.missouri.edu/)
- Civil and Environmental Engineering (https://engineering.missouri.edu/academics/civil/)
Expected start dates are Spring or Fall of 2022. The successful candidates will have opportunities to pursue independent research in one or more of the following research projects:
1) Developing, testing and validating hydrologic, hydraulic and biogeochemical cycling models for watersheds in the Mississippi River Basin, and incorporating machine learning and other novel search algorithms to offer innovative solutions to problems pertaining water availability, watershed management and water quality.
2) Developing integrated assessment models to evaluate the economic benefits of water resources infrastructure (dams, reservoirs, levees, irrigation canals, conservation practices and green infrastructure, etc.) on mitigation and risk reduction due to climate change, soil erosion, and enhance public access to water supplies.
3) Compiling existing instrumentation and monitoring technologies, and developing data integration technologies to aid in testing, validating, and improving ecosystem model simulations/predictions.
4) Developing holistic analytical decision support tools that account for water use, environmental conservation practices, and climate change adaptation among others to evaluate new technologies for aiding sustainable resources management and precision agriculture in the Missouri River Basin.
5) Evaluating the impacts of wetland enhancement and flooding on water table dynamics and nitrate transport in mixed agricultural and natural landscapes. Research activities include field instrumentation, monitoring, and modeling ground- and surface- water interactions.
6) Developing field instrumentation (e.g., unmanned aerial systems, large aperture scintillometers, weather stations, soil moisture sensors, among others) and integrating cloud-based data visualization technologies to monitor, estimate, and predict ecosystem fluxes across multiple managed landscapes in the Missouri River Basin.
7) Evaluating deficit irrigation methods to improve water management in small-scale producer systems. Research activities include setting up and monitoring smallholder agricultural plots at the University of Missouri Agricultural Experimental Station.
Successful applicants are expected to conduct high-quality research, present research findings at conferences, publish in peer-reviewed journals, and assist in teaching. A competitive stipend, tuition waiver, and health benefits will be provided to qualified candidates.
Qualifications: MS degree in a science or engineering discipline (e.g., Agricultural, Biological, Civil and Environmental Engineering, Environmental Sciences, Atmospheric Sciences, Mathematics, Physics or related field). Highly motivated and qualified students with BS degrees will also be considered. Strong writing, quantitative, and analytical skills are essential. Successful candidates will be creative, motivated, and capable of working independently as well as collaboratively.
Location: All positions are located in Columbia, Missouri, and will require travel to multiple field locations. Successful candidates will join a dynamic and interactive group of students and faculty at the University of Missouri’s various academic divisions including BBCE, SNR, IDSI and CEE. Students will also have opportunities for collaborative research with federal scientists at USDA-ARS Hydraulic Engineering Research Unit, USDA-ARS Cropping Systems and Water Quality Research Group, USGS Columbia Environmental Research Center, and Missouri Cooperative Fish and Wildlife Research Unit.
Contact: For more information about the positions, please contact Noel Aloysius at firstname.lastname@example.org
Application Instructions: Please email Noel Aloysius (email@example.com) in a single PDF: 1) A letter of interest that briefly describes educational and research background, as well as research interests/goals (1-2 pages); 2) A curriculum vitae that also includes, if applicable, TOEFL/IELTS scores; 3) Unofficial copies of transcripts; and 4) Contact information of three professional references (referees will not be contacted initially). Please write “Graduate Research Position 2021/22” in the subject line. Review of applications will begin immediately.
Diversity Commitment: The University of Missouri is fully committed to achieving the goal of a diverse and inclusive academic community of faculty, staff and students. We seek individuals who are committed to this goal and our core campus values of respect, responsibility, discovery and excellence. The University of Missouri is an equal opportunity/affirmative action employer.
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: https://bondlsc.missouri.edu/research/life-sciences-fellowship/
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, MUIDSI 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 MUIDSI
Contact: Mr. Robert Sanders (firstname.lastname@example.org)
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:
- 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;
- Develop a universal influenza vaccine, optimize vaccine production and vaccination strategies for disease prevention and quarantine;
- Develop machine learning methods to predict vaccine efficacy for each individual based on personal data, a move towards precision medicine;
- 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 (email@example.com)