Jobs · Analyst · Oklahoma

Postdoctoral Fellow in Biology AF9026

Oklahoma State University · Stillwater, OK · 1 wk ago
Analyst$57k/yrTemporary

Contact: Dr. Michael Reichert, michael.reichert@okstate.edu

Hiring range: $57,000. Start date flexible, as early as October 15, 2026.

About the role

The Reichert lab in the Department of Biology at Oklahoma State University is seeking a postdoctoral researcher to work on an NSF-funded project on the energetic drivers of individual variation in animal communication behavior. The project focuses on the relationship between metabolic rate and acoustic signaling behavior in gray treefrogs and will involve:

  • Field recordings of acoustic signals
  • Playback experiments to assess behavioral plasticity
  • Measurement of metabolic rate using respirometry
  • Investigations of the genetic basis of metabolic and behavioral phenotypes

The postdoc will lead data collection, develop new projects aligned with their interests and grant aims, communicate results through publications and presentations, and contribute to student mentorship. The lab is dedicated to professional development, offering opportunities in teaching, mentorship, and outreach, and fosters a supportive research environment for all members.

Responsibilities

  • Lead data collection for project experiments
  • Develop new research projects in line with grant aims and personal interests
  • Publish and present scientific results
  • Mentor students
  • Collaborate with the PI and team in field and lab settings

Requirements

  • Ph.D. in ecology, evolution, behavior, or a related field (must be conferred by start date)
  • Experience working on large-scale research projects
  • Experience with data curation, analysis, and scientific publication
  • Ability to work collaboratively in lab and field settings

Preferred Qualifications

Candidates with experience in any of the following are especially encouraged to apply:

  • Bioacoustics
  • Behavioral energetics
  • Behavioral genetics
  • Individual behavioral variation
  • Advanced mixed modeling techniques

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