Lab info

Help with lab research!

One of three deep-learning rigs available as your new workstation!

The Behavioral Complexity Lab is looking for highly dedicated and inquisitive undergrads to help with an enormous backlog of data (from both long-in-the-tooth projects and current ones). Though we have many research avenues for you to help with and explore, we highly value creativity in research. So, we encourage you to work with us for a while and use our work as inspiration for something novel and exciting!

We are also actively looking for undergraduates interested in getting paid to do their research. Opportunities to have your undergraduate research fully funded are available through the Wyoming Research Scholars Program and the UW Honors College, among others. We will work with you to find an ideal project that fits the research goals of the Behavioral Complexity Lab, and then we will help you apply for funding!

We need help in the following areas:

Preparation for next field season:

  • Designing and 3D printing molds to create artificial soy-wax bird eggs for field experiment in Panama
  • Redesign of bite-force transducer to measure bite-force of insectivorous birds in Panama
  • Preparation of acoustic playback trials to test impacts of noise on avian signals in Panama forests
Or, if with just a little bit of funding, the tropical forest will be your office.

Data transcription and annotation:

  • Transcription of playback observations (digital files) from several experiments on birds in Panama and Galapagos.

New data management and analysis:

  • Organizing incoming datastreams from the UW Bird-Window Collision Project.
  • Cataloging bird plumage photographs for calibrated color analysis.
  • Analysis of bird song/call structure (acoustic analysis)
  • Online literature searches.
  • Website and computer management (included working with Linux and one very expensive deep-learning computer)

New project development:

  • Working with Principal Investigator to complete the development of a new R package (must have knowledge of GitHub)
  • Developing several reproducible machine learning (deep learning) workflows for sound, image, and text analysis.

Analysis of existing datasets

  • Environmental predictability and nesting of tropical birds (requires knowledge of R)
  • Individual distinctiveness of suboscine bird song (requires acoustic analysis)
  • Impacts of insect noise on dawn chorusing of birds (a re-analysis)
  • Species associations using acoustic logger data
  • Simulations of animal surveys to optimize survey design

The BCL has countless other projects if you are interested. Many of these projects are in their infancy and will require you to develop tools for organizing and processing raw data.