NOTE: It is recommended to log in with your UMN Credentials using the "UMN Login" in the top right before clicking "Apply".
Eligibility
Applicants must be a PhD candidate student at the University of Minnesota. Post-docs are not eligible for this assistantship program. The student’s preliminary oral exam must also be completed by the start of the appointment (typically no later than June 1st, 2024).
Program Description
The Data Science Initiative-MnDRIVE Graduate Assistantship program supports UMN PhD candidates pursuing research at the intersection of Data Science and any of the five MnDRIVE areas: Robotics, Sensors and Advanced Manufacturing; Global Food Ventures; Advancing Industry, Conserving Our Environment; Discoveries and Treatments for Brain Conditions; and Cancer Clinical Trials.
"Data science" in this case is defined broadly as the collection of approaches and disciplines encompassing the entire data pipeline. Proposals must align with one of the Data Science tracks:
Foundational Data Sciences: Topics that are foundational to data science applications including data-intensive and data-informed topics and applications along with methodological research in areas such as signal processing, data mining, machine learning, artificial intelligence as well as topics in ethics and privacy. Fundamental methods dealing with data storage, archiving, sharing, acquisition, compression, or transmission are included. This includes, but is not limited to, disciplines that underlie data science such as statistics, mathematics, computer science, philosophy, and social and behavioral sciences.
- Digital Health and Personalized Health Care Delivery: The broad scope of digital health includes disciplines such as mobile health (mHealth), public health, health information technology (HIT), wearable devices or tech, telehealth and telemedicine, and personalized healthcare and medicine. It includes enhancements to patient and consumer health and healthcare delivery through capacity-building activities and continuous, personalized, predictive, participative, and preventive approaches.
The program aims to support approximately ten 12-month research assistantships for a 12-month (2 semesters and 1 summer), 50% graduate research assistantship, including tuition for up to 14 credits each semester (Fall & Spring) and subsidized health insurance through the Graduate Assistant Health Plan. Depending on the number of applicants and the availability of funding, smaller stipends may also be offered. Applications for assistantships may begin as early as the following Spring term and must be started by June 1 of the year following the submission of your application. Graduate students are expected to have successfully completed their preliminary oral exam by the start of the appointment. Depending on the availability of funding, awards may include up to $1,500 for travel to a conference or to defray costs for specialized training support if they are directly related to the proposed research. A final report of accomplishments made possible by this support is expected after the completion of this award.
Selection Criteria
Applicants will be selected based on academic record, potential for future research productivity, and impact on the areas of the MnDRIVE initiative (see mndrive.umn.edu for the goals of each area).
Application Checklist
The application process will require the submission of the following materials.
Public-facing project abstract (200 word limit) (If funded, this abstract will be used to create a Research Computing Project Highlight story.)
1-page research plan (single-spaced, 11-point font), describing alignment with MnDRIVE goals and intersection with data science
1-page personal statement (single-spaced, 11-point font), describing how this award will advance your career and meet the goals of MnDRIVE
Curriculum Vitae, which includes previous education, relevant work experience, honors/awards, research experiences, publication, and conference abstract titles
Unofficial transcript
Two letters of recommendation (each letter should be no more than 2 pages): Applicants should arrange for two letters recommendation, one of which must be from the applicant's faculty advisor. The letters should comment on the applicant’s potential for future research productivity. The faculty advisor should (i) include confirmation that they will continue to be the advisor of the applicant during the period of funding, (ii) confirm that the applicant will have reached doctoral candidacy by the start of the award, (iii) confirm the research plan, and (iv) explain the impact or implications of the research for at least one MnDRIVE area.
Completed applications and recommendation letters must be submitted through this application portal by no later than October 6 at 5:00pm CST. Late applications will not accepted. Fellowship awards will be announced by early December.
For questions, please contact dsi-grants@umn.edu
DSI-MnDRIVE PhD Graduate Assistantship Program 2024
NOTE: It is recommended to log in with your UMN Credentials using the "UMN Login" in the top right before clicking "Apply".
Eligibility
Applicants must be a PhD candidate student at the University of Minnesota. Post-docs are not eligible for this assistantship program. The student’s preliminary oral exam must also be completed by the start of the appointment (typically no later than June 1st, 2024).
Program Description
The Data Science Initiative-MnDRIVE Graduate Assistantship program supports UMN PhD candidates pursuing research at the intersection of Data Science and any of the five MnDRIVE areas: Robotics, Sensors and Advanced Manufacturing; Global Food Ventures; Advancing Industry, Conserving Our Environment; Discoveries and Treatments for Brain Conditions; and Cancer Clinical Trials.
"Data science" in this case is defined broadly as the collection of approaches and disciplines encompassing the entire data pipeline. Proposals must align with one of the Data Science tracks:
Foundational Data Sciences: Topics that are foundational to data science applications including data-intensive and data-informed topics and applications along with methodological research in areas such as signal processing, data mining, machine learning, artificial intelligence as well as topics in ethics and privacy. Fundamental methods dealing with data storage, archiving, sharing, acquisition, compression, or transmission are included. This includes, but is not limited to, disciplines that underlie data science such as statistics, mathematics, computer science, philosophy, and social and behavioral sciences.
- Digital Health and Personalized Health Care Delivery: The broad scope of digital health includes disciplines such as mobile health (mHealth), public health, health information technology (HIT), wearable devices or tech, telehealth and telemedicine, and personalized healthcare and medicine. It includes enhancements to patient and consumer health and healthcare delivery through capacity-building activities and continuous, personalized, predictive, participative, and preventive approaches.
The program aims to support approximately ten 12-month research assistantships for a 12-month (2 semesters and 1 summer), 50% graduate research assistantship, including tuition for up to 14 credits each semester (Fall & Spring) and subsidized health insurance through the Graduate Assistant Health Plan. Depending on the number of applicants and the availability of funding, smaller stipends may also be offered. Applications for assistantships may begin as early as the following Spring term and must be started by June 1 of the year following the submission of your application. Graduate students are expected to have successfully completed their preliminary oral exam by the start of the appointment. Depending on the availability of funding, awards may include up to $1,500 for travel to a conference or to defray costs for specialized training support if they are directly related to the proposed research. A final report of accomplishments made possible by this support is expected after the completion of this award.
Selection Criteria
Applicants will be selected based on academic record, potential for future research productivity, and impact on the areas of the MnDRIVE initiative (see mndrive.umn.edu for the goals of each area).
Application Checklist
The application process will require the submission of the following materials.
Public-facing project abstract (200 word limit) (If funded, this abstract will be used to create a Research Computing Project Highlight story.)
1-page research plan (single-spaced, 11-point font), describing alignment with MnDRIVE goals and intersection with data science
1-page personal statement (single-spaced, 11-point font), describing how this award will advance your career and meet the goals of MnDRIVE
Curriculum Vitae, which includes previous education, relevant work experience, honors/awards, research experiences, publication, and conference abstract titles
Unofficial transcript
Two letters of recommendation (each letter should be no more than 2 pages): Applicants should arrange for two letters recommendation, one of which must be from the applicant's faculty advisor. The letters should comment on the applicant’s potential for future research productivity. The faculty advisor should (i) include confirmation that they will continue to be the advisor of the applicant during the period of funding, (ii) confirm that the applicant will have reached doctoral candidacy by the start of the award, (iii) confirm the research plan, and (iv) explain the impact or implications of the research for at least one MnDRIVE area.
Completed applications and recommendation letters must be submitted through this application portal by no later than October 6 at 5:00pm CST. Late applications will not accepted. Fellowship awards will be announced by early December.
For questions, please contact dsi-grants@umn.edu