Graduate Position in Aquatic Ecosystem Monitoring – Texas

Baylor University
Waco, TX
Job Category
Graduate Assistantships
$25K (with benefits)
Start Date
Last Date to Apply
The Department of Environmental Science at Baylor University offers graduate program degrees for Master of Science or Doctor of Philosophy in Environmental Science. The McManamay lab at BU is a highly interdisciplinary group that generally studies human-environmental interactions related to water resources and impacts of anthropogenic disturbances on aquatic ecosystems and biodiversity. Our research includes a mixture of spatial ecology and biogeography, integrated field-modeling analysis, ecosystem assessment, hydrography, and decision-support. One of our focus areas is studying long-term dynamics in fish and invertebrate community responses to restoration and environmental variation. Dr. Ryan McManamay at BU is seeking an M.S. or Ph.D. student to start January 2020 to study novel mechanisms of cataloguing aquatic biodiversity through imaging and deep learning. Through collaboration with Oak Ridge National Laboratory and the Department of Computational Sciences at BU, the student will examine the potential effectiveness of an autonomous imaging system and associated software for identifying invertebrate and fish taxa to inform biomonitoring efforts. Students will also have access to long-term datasets of fish and invertebrate communities for further scientific inquiry and participate in biological monitoring programs proximate to Baylor. To apply, please email Dr. Ryan McManamay ( by 9/30/2019 with (1) CV, (2) letter of intent with goals and research experience, and (3) contact information for 2 references. For interested PhD students, please include goals for graduate study including interest in studying long-term ecological community dynamics.
Students with experience in invertebrate and fish collection and monitoring are desired skills. Additionally, students with experience with image analysis and/or familiarity with programming languages capable of analyzing imagery (e.g., R, python, or C++) are encouraged to apply.
Contact Person
Dr. Ryan McManamay
Contact eMail
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