The Youngflesh Lab in the Department of Biological Sciences at Clemson University is seeking 1-2 PhD students to join the lab in Fall 2026. The lab's research focuses on quantitative ecology, biodiversity conservation, and population biology, with a strong emphasis on using advanced data science tools such as hierarchical Bayesian modeling and AI to address questions in global change ecology. Potential research topics include drivers of biodiversity, demographic and life history dynamics, and phenological responses across space, time, and species. Projects will leverage large-scale data resources, including community science projects, satellite sensors, and long-term field studies. Applicants should have a bachelor's degree in ecology, statistics, computer science, or a related field, and possess strong quantitative skills or a strong motivation to develop them. Experience with R, hierarchical Bayesian modeling, deep learning, and large-scale data analysis is advantageous. The lab values excellent communication skills, a collaborative and respectful attitude, and a passion for biodiversity and global change research. Prior experience with birds or marine mammals is a plus but not required. The lab is committed to building a diverse team and encourages applications from historically underrepresented groups. PhD students will be fully supported through teaching and research assistantships, with an annual stipend of $27,000 to $30,000. Students are also encouraged to apply for external fellowships such as the NSF GRFP and NASA FINESST. Clemson University is a public R1 research university located in the biodiversity-rich foothills of the Blue Ridge Mountains in South Carolina, USA. The lab offers rigorous training in ecology, data science, science communication, and project management, and supports a variety of career paths in academia, government, NGOs, and data science. To apply, prospective students should email Dr. Casey Youngflesh with a cover letter, writing sample, and CV, using the subject line 'Prospective PhD Student.' The application deadline is December 1, 2025, but early contact is encouraged. More information is available on the lab's website.