The core objective of this study is to implement and evaluate novel visual and structural treatments on existing wildlife crossing structures (specifically, double-box culverts, or CBCs) to increase their permeability to wildlife.
The successful candidate will lead research to determine if the application of these modifications affects the usage and crossing success rates of wildlife, particularly deer and other ungulates, through these structures. The findings will directly inform state transportation policy regarding wildlife-vehicle collision mitigation.
4/14/2026
The researcher will execute the following tasks under the direction of Dr. Bombaci:
1. Literature Review
- Conduct a comprehensive review and synthesis of the current state of knowledge regarding ungulate perception, color vision, wildlife crossing structure design, and the effectiveness of existing CBC treatments.
2. Experimental Site Selection and GIS Analysis
- The GRA will utilize GIS to analyze wildlife-vehicle collision (WVC) data, conduct field evaluations of multiple culvert locations on fenced state highways, and finalize the selection of experimental sites.
3. Treatment Implementation and Field Setup
- Coordinate with the research team and CDOT to design and physically apply the experimental treatments.
4. Data Collection, Analysis, and Dissemination
- Deploy, maintain, and manage a network of motion-triggered cameras to monitor ungulate presence, movement, and crossing success at all CBCs
Review academic literature, GIS Analysis, apply paint treatments, deploy camera traps
Pass background check.
Carries out duties as instructed.
Dr. Sara Bombaci
Bachelor’s degree in Wildlife Biology, Ecology, Environmental Science, or a closely related field.
Minimum GPA of 3.0.
Proven ability to conduct fieldwork in outdoor environments, including remote camera setup and maintenance.
Strong written and verbal communication skills.
Strong work ethic.
Demonstrated proficiency in GIS software or R for spatial data management, analysis, and visualization.
Experience with statistical analysis (e.g., R, SPSS, or similar).
Experience with independent research, presentations of research, or publications.
To apply, please upload the following applicant documents. Ensure your materials fully address the required and preferred job qualifications of the position. Please note, applicants may redact information from their application materials that identifies their age, date of birth, or dates of attendance at or graduation from an educational institution.
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