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Research Scientist

Job in Minneapolis, Hennepin County, Minnesota, 55415, USA
Listing for: University of Minnesota
Full Time, Per diem position
Listed on 2026-06-11
Job specializations:
  • Research/Development
    Data Scientist
Job Description & How to Apply Below
About the Job

We seek a highly motivated individual to serve in the Runck Lab in a temporary and casual capacity. The successful candidate will support on-going research and development in one or more of the following areas: electrical or computer engineering, data analysis, modeling, machine learning, geographic information systems (GIS), software development, sensing systems, or related fields. Specific duties will be matched to the candidate's background and the lab's current project needs.

This is a temporary and casual research support role. Specific responsibilities will be tailored to the candidate's expertise and the lab's project needs, and may include any combination of the following:

* Research and Development Support (100%)

* Support research, development, prototyping, testing, and analysis activities across the lab's project portfolio, which may include hardware and firmware systems, software tools, data pipelines, modeling and machine learning workflows, geospatial analysis, or sensor deployment and monitoring.

* Support the production of professional and policy outputs such as scientific documentation, tutorials, standard operating procedures, online content, journal articles, books, book chapters, and presentations.

* Support data organization, processing, quality assurance, and visualization for active research projects.

* Support the deployment, maintenance, and decommissioning of field-deployed systems as needed.

Qualifications

Required Qualifications:

* Bachelor's degree (or higher) in a field relevant to the work, such as electrical, computer, or mechanical engineering; computer science; data science; statistics; geography or GIS; environmental, agricultural, or natural sciences; or a closely related field.

* Demonstrated experience relevant to one or more of the lab's core areas: hardware/firmware development, software development, data analysis, modeling, machine learning, or geospatial analysis.

* Good written and verbal communication skills.

* Ability to work both independently and collaboratively in a multidisciplinary team environment.

Preferred Qualifications:

* Experience with one or more programming or analysis tools commonly used in the lab (e.g., Python, R, C/C++, SQL, MATLAB).

* Experience with environmental sensing systems, embedded systems, or Internet of Things (IoT) hardware.

* Experience with data visualization, dashboarding, or database management

About the Department

The Runck Lab focuses on the science and engineering of real-time geoinformation systems ranging from data collection (hardware, firmware) through to data storage, modeling, and visualization. On-going work focuses on the application of novel spatial machine learning and artificial intelligence models in real-time to support decision-making, the development of novel sensing modalities, and the effects of geovisualization systems on cross-organization decision-making and action.

Funding for the lab comes from diverse sources including recurring funding through the GEMS Informatics Center from the MnDRIVE program, federal grants, state grants, foundations, and private companies. The lab fluctuates between 8 and 12 members with two full-time research staff supporting lab operations and GEMS Sensing, a service organization focused on research support for environmental data collection. Due to the applied and cross-sector nature of R&D, the lab provides an opportunity to broadly engage in large, multidisciplinary, and high impact R&D.

The GEMS Informatics Center is a joint initiative of the College of Food, Agriculture and Natural Resource Sciences and the Minnesota Supercomputing Institute and is a highly diverse international and interdisciplinary team of professionals. The Center is re-imagining the relationships between data, institutions, and disciplines to inform and accelerate innovation within the food and agricultural sectors. GEMS broadly seeks to make genomics, environmental, management, and socioeconomic data inter-operable at varying spatial and temporal scales to generate actionable information and promote new innovation partnerships that accelerates and sustains growth in local and global food and…
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