Duration: Summer 2021 (schedule and hours TBD)
Location: Remote.
Duties: This internship will allow the student some flexibility.
assist staff scientists and data managers with specific data projects, statistical analyses, and literature searches
organize and prepare data or other research outputs for ingest in the data repository
work with tools that facilitate structured metadata
Learning Outcomes:
These are a few possible learning outcomes, which will vary by project and previous experience:
- learn how to identify & evaluate data published in scientific literature
- learn how to effectively clean and organize data for analysis
- learn analytics best practices for reproducible data science
- gain experience working with R, Python, GIS, and other computational tools & software
- gain experience working with longitudinal and spatial data
- gain experience applying machine learning to biological/ecological datasets
- learn how to publish data
Compensation: This internship is unpaid, although in some special cases (e.g., for grant-funded projects) compensation may be available. We will work with academic institutions to provide credit for this internship.
Preferred Qualifications:
Ideal candidates will:
- have some experience using R, Python, GIS, relational databases, or similar tools
- have experience working with scientific or technical data
- have excellent organizational skills
- be able to work independently and communicate clearly
- be familiar with common office applications (e.g. spreadsheets)
The qualifications above are preferred, not required. We would like to hear about other skills, strengths, and experiences you bring to the job!
A background in environmental science or other scientific discipline is preferred.
Contact: Amy Schuler schulera@caryinstitute.org