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 focuses on quantitative ecology, using advanced data science and statistical tools to address questions in global change ecology, biodiversity, and population biology. Research topics may include drivers of biodiversity, demographic and life history dynamics, and phenological responses across species and environments. Projects leverage large-scale data resources such as community science projects, satellite sensors, and long-term field studies, with a strong emphasis on computational approaches including hierarchical Bayesian modeling and AI.

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. Students from diverse backgrounds and underrepresented groups are especially encouraged to apply. The GRE is not required for application.

PhD students will be fully funded through teaching and research assistantships, with an annual stipend of $27,000 to $30,000 and tuition coverage. Students are also encouraged to apply for external fellowships such as the NSF GRFP and NASA FINESST. The lab provides 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. The lab environment emphasizes mentorship, structured goal-setting, and work-life balance.

To apply, prospective students should email Dr. Casey Youngflesh with a cover letter, writing sample, and CV, using the subject line 'Prospective PhD Student.' Competitive applicants will be invited for a Zoom interview. The application deadline is December 1, 2025. For more information, visit the lab's opportunities page.