Fisheries Research Assistant — Telemetry Data

Lower Wisconsin River Trap-and-Transfer Project

Description: During 2025 and 2026, in collaboration with Alliant Energy and the Wisconsin DNR we captured and transferred 50 blue suckers, 50 shovelnose sturgeon, and 20 lake sturgeon above Prairie Du Sac Dam on the Lower Wisconsin River to determine their behavior after transfer. Each fish was implanted with an acoustic transmitter. The student will largely be responsible for analysis of telemetry data using capture-recapture models with some field work associated with active tracking and downloading of acoustic receivers.

Qualifications: BS in Fisheries, Biology, Ecology or related field with GPA ≥ 3.0. Familiarity with acoustic telemetry data and using R preferred as this is largely an analytical exercise. However, some experience launching and navigating boats would be beneficial.

Description: During 2025, in collaboration with the Wisconsin and Michigan Departments of Natural Resources, acoustic transmitters were implanted into 140 walleye in northern Green Bay and 50 walleye from the Sturgeon Bay area to determine spawning locations. This project will involve extensive field work in 2027 and 2028 to download receivers and determine where eggs are deposited in the Sturgeon Bay area and whether larvae hatch at these locations.

The project will also require analysis of a large telemetry data set.

Qualifications: BS in Fisheries, Biology, Ecology or related field with GPA ≥ 3.0. Extensive experience launching and navigating boats in a large lake environment is preferred. Some familiarity with the R programming language also preferred. Experience with acoustic telemetry technology and data would be beneficial.

Description: We will use population information, Floy tag recovery information, and acoustic telemetry data collected by the Missouri Department of Conservation (MDC) for shovelnose sturgeon in the Mississippi and Missouri rivers to estimate and compare mortality rates for different river segments. This project is largely an analytical exercise that will focus on using length-based and capture-recapture models.

Qualifications: Familiarity with the R programming language preferred. Experience with acoustic telemetry technology and data would also be beneficial.

Stipend: $20,000 and tuition is paid

January 1, 2027

To apply, please email cover letter, CV/resume, unofficial transcripts, and contact information for three references to Daniel Isermann (dan.isermann).

July 25, 2026