Intern- Grad Kern Center

Mayo Clinic•Rochester, MN

1d•Hybrid

About The Position

Informatics and Data Science interns provide data and informatics insights for business problems that can be approached with analytics techniques to collect, explore, and extract insights from structured and unstructured data. Will develop an understanding of the ways in which information (i.e. meaningful data) is converted into knowledge. May identify substantive problems where different representations, algorithms, and methods can be used to inform practice. May perform detailed analysis of large bodies of heterogeneous data in order to discover new patterns and insights having an impact upon patient health and augmenting human capabilities. May collaborate on data collection methods, data query scripting, data analysis, data engineering, as well as the application of appropriate AI methods for analysis, visualizations, and forecasting under the direction of the scientific project lead and/or mentor. Innovation and design interns will focus on building skills in design research and service design, while providing exposure to the role of design in health care. Responsibilities include supporting the staff design researchers with primary and secondary research activities. This may include direct patient contact with care teams in the clinical setting, planning and conducting research activities with an emphasis on rigorous documentation and visualization. Engineering interns will work in the context of human factors engineering and system integration or information decision engineering, performed in a multi-disciplinary environment under the direction of a principal investigator. One or more mentors will be assigned to provide instruction, guidance, and to assess performance. Projects may include contact with study participants and staff in a simulated or clinical setting, planning and conducting data collection activities, and analysis activities. Health Care Delivery Research intern work will be focused on building skills in research. Responsibilities may include: conducting literature reviews to support projects; assisting staff in the review, identification, and development of research findings; participating in the collection, analysis, and review of research data; developing spreadsheets and databases to support project activities; and analyzing data to contribute to the reporting and interpretation of research findings. Projects may include contact with study participants and multidisciplinary teams.

Requirements

Must live within 100 miles driving distance to campus.
This vacancy is not eligible for sponsorship / we will not sponsor or transfer visas for this position.

Responsibilities

Provide data and informatics insights for business problems using analytics techniques to collect, explore, and extract insights from structured and unstructured data.
Develop an understanding of how information is converted into knowledge.
Identify problems where different representations, algorithms, and methods can be used to inform practice.
Perform detailed analysis of large bodies of heterogeneous data to discover new patterns and insights impacting patient health and augmenting human capabilities.
Collaborate on data collection methods, data query scripting, data analysis, data engineering, and the application of AI methods for analysis, visualizations, and forecasting.
Support staff design researchers with primary and secondary research activities.
Engage in direct patient contact with care teams in the clinical setting.
Plan and conduct research activities with an emphasis on rigorous documentation and visualization.
Work in the context of human factors engineering and system integration or information decision engineering.
Conduct literature reviews to support projects.
Assist staff in the review, identification, and development of research findings.
Participate in the collection, analysis, and review of research data.
Develop spreadsheets and databases to support project activities.
Analyze data to contribute to the reporting and interpretation of research findings.