Graduate Position / Research Associate: Seabird bycatch in Northeastern US and Atlantic Canada (VA)
Virginia Tech is searching for a graduate student (Ph.D. or MSc) or research associate to join a funded research project aimed at improving the understanding of seabird bycatch, particularly Great Shearwater (Ardenna gravis) and Northern Gannets (Morus bassanus), in commercial fisheries in the Northeastern U.S. and Atlantic Canada. Deadline to apply: ASAP!
Agency/Organization: Fish and Wildlife Conservation, Virginia Polytechnic Institute and State University (Virginia Tech)
Location: Blacksburg, Virginia
Website: Click here
Job Description: The position will begin in January 2024. The successful candidate will join a funded research project aimed at improving the understanding of seabird bycatch, particularly Great Shearwater (Ardenna gravis) and Northern Gannets (Morus bassanus), in commercial fisheries in the Northeastern U.S. and Atlantic Canada. The candidate will collaborate with team members, including a soon-to-be-hired postdoc, to request and organize observer program and logbook data from multiple fisheries, develop spatiotemporal models to identify factors influencing seabird bycatch, and evaluate the effectiveness of potential bycatch reduction strategies through simulations.
Qualifications:
Requirements:
- MSc or BSc in fisheries, biology/ecology, statistics, computer science or a related field
- Self-motivated and capable of working independently and collaboratively
- Strong oral and written communication skills
Preferred qualifications: We are looking for candidates with strong programming skills, and experience in data analysis, particularly related to ecological modeling or fisheries research. The ideal candidate will possess:
- Proficiency in R, Python, or MATLB
- Familiarity with spatiotemporal analytical methods and software
- Experience in ecological modeling, population dynamics, and fisheries management
- Knowledge of species distribution models, catch rate standardization, or stock assessment models
- Experience in statistical modeling in both frequentist and Bayesian frameworks
- A strong publication record
Wage: N/A
To apply: Application materials should be emailed to Dr. Yan Jiao at yjiao@vt.edu. Please submit a single PDF file that includes your CV and the names and contact information for three references.
Application Deadline: ASAP: as soon as a suitable candidate is found. Review begins immediately.
Start Date: January 2024
Contact: Dr. Yan Jiao (yjiao@vt.edu)
