Quantitative and Evolutionary STEM Training (QuEST) Program for Doctoral Students

We are seeking trainees passionate about developing tools for pressing environmental and global health problems. Does this sound like you?

You will learn:

  • A strong understanding of core concepts in evolution, ecology, and epidemiology

  • Exposure to contemporary, real-world topics where modeling and predicting system disturbances are crucial

  • Skill development for hypothesis and experimental design, and interdisciplinary teamwork and communications training

Application Details

  • Prerequisite: currently enrolled or incoming UVM PhD students from the following fields and programs: Mathematics & Statistics, Rubenstein School of Environment and Natural Resources, Biology, Plant biology, Plant and soil sciences, Complex systems, Computer science and any other related fields/programs.
  • Complete and submit a QuEST online application to apply for a traineeship. Or download the application using Word (docx). Email the completed application to Lola.Chen@uvm.edu. Applications received by July 16, 2023 will be given highest priority.
  • Application deadline: August 7th, 2023

    For questions, please email Lola Chen at Lola.Chen@uvm.edu,  QuEST Program Coordinator.


    QuEST Leadership and The University of Vermont are especially interested in students who contribute to the inclusion, diversity, and excellence of the academic environment both professionally and personally.

    Students from diverse educational backgrounds (e.g., biology, mathematics, and computer science, agricultural, environmental, and health sciences, STEM education) and work-life experiences (e.g. community college, extracurricular, volunteerism), women, LGBTQ, and first-generation college, veterans, and individuals with disabilities, and underrepresented racial, ethnic, gender, socio-economic and cultural groups are strongly encouraged to apply. 

    Made possible by a National Science Foundation Research Traineeship grant to the University of Vermont.