Bioacoustics Internship 

The Smithsonian’s National Zoo and Conservation Biology Institute (SNZCBI) is seeking one intern to assist with processing and analyzing bioacoustic data collected from research projects in Borneo and Montana. These projects support ongoing biodiversity monitoring at ecological restoration sites and focus on estimating the relative abundance of indicator species (e.g., grassland birds in Montana; hornbills and primates in Borneo).

The selected intern will work closely with Smithsonian scientists to process, validate, and summarize large acoustic datasets using platforms such as Arbimon and BirdNET. Responsibilities will include reviewing automated detections, conducting quality control on species classifications, organizing structured datasets for analysis, and generating summary outputs for scientific and stakeholder reporting.

The intern will use R (RStudio) to manage, clean, visualize, and summarize data, and will be expected to work within reproducible workflows. Additional opportunities include contributing to analytical code development, assisting with stakeholder report preparation, and participating in other conservation research activities within the SNZCBI Field Ecology Lab.

This position is primarily office-based with limited fieldwork. The internship will be conducted in person at the Smithsonian Conservation Biology Institute in Front Royal, Virginia.

Website: https://nationalzoo.si.edu/conservation

Stipend and Housing

This position includes a $2,000/month stipend. Optional on-site housing is available at $9/day in a communal dormitory setting.

Duration

This internship is approximately six months, beginning in early June 2026 and ending in early January 2027. There may be potential for extension depending on funding availability.

Required Qualifications

• Recent completion of a B.S. or M.S. in Wildlife Biology, Ecology, Conservation Biology, Environmental Science, or a closely related field
• Demonstrated interest in bioacoustics, biodiversity monitoring, or quantitative ecology
• Experience managing and analyzing ecological or biological datasets
• Working proficiency in R, including data wrangling, visualization, and basic statistical summaries
• Experience working with structured data files (e.g., CSV, Excel) and maintaining organized, reproducible workflows
• Strong attention to detail and ability to conduct careful quality control on large datasets
• Ability to work both independently and collaboratively in a research environment
• Willingness to help with other field projects as needed

Preferred Qualifications

• Experience with bioacoustic tools or acoustic data processing platforms (e.g., Arbimon, BirdNET, Raven, Kaleidoscope)
• Experience validating automated species detections or working with machine learning–generated outputs
• Familiarity with Python for data processing (beneficial but not required)
• Experience working with large or multi-site ecological datasets
• Experience contributing to technical reports or scientific outputs