University of Michigan

What you'll study

This PhD emphasises original research supported by a foundation of advanced coursework and methodological training. Core subjects commonly taken by students include evolutionary theory, population genetics and genomics, phylogenetic methods, community and ecosystem ecology, quantitative ecology and ecological modelling, and statistical methods for ecological and evolutionary data (e.g. Bayesian inference, mixed models, multivariate analyses).

Programme structure typically includes initial coursework and seminars, rotation-style research experiences or short-term projects to identify a dissertation advisor, qualifying examinations or a research proposal defence, and then a sustained dissertation research period. Training is flexible and may incorporate laboratory work (molecular methods, genomics), field ecology (design and execution of field experiments, long-term observational studies), museum- and collection-based research (systematics, morphometrics), and intensive computational approaches (population genetic simulation, phylogenomic inference, ecological forecasting).

Students also develop professional skills through teaching opportunities, presentation of work at seminars and conferences, and workshops on grant writing, data management and reproducible research. Interdisciplinary collaborations across departments and centres (for example, with bioinformatics, statistics, conservation science or climate science groups) are encouraged.

Entry requirements

Applicants are normally expected to hold a strong undergraduate degree in biology, ecology, evolutionary biology or a closely related discipline; many applicants hold a master’s degree and relevant research experience. Competitive applicants demonstrate coursework in genetics, ecology and statistics or mathematics, and practical experience with field or laboratory research methods.

• Academic transcripts showing strong performance in relevant science courses.
• A research-focused statement of purpose outlining past experience, research interests and potential fit with departmental strengths.
• A curriculum vitae listing research projects, publications, presentations and relevant technical skills.
• Three letters of recommendation from academic or research supervisors who can speak to research ability and potential for doctoral study.
• Evidence of quantitative skills (coursework, coding experience, or analysis projects) is highly recommended.
• International applicants must meet the university’s English language proficiency requirements.

Standardised test requirements vary by year and applicant background; prospective students should consult the programme’s admissions page for current guidance. Most admitted students enter with demonstrated research independence or a clear plan for dissertation research.

Career prospects

Graduates move into a wide range of careers that leverage their research, analytical and communication skills. Common pathways include tenure-track academic positions in ecology and evolution, postdoctoral research in academic or national laboratory settings, and research scientist roles in museums and botanical gardens.

Outside academia, alumni find roles in conservation and natural resource management (non-governmental organisations, government agencies), environmental consultancy, biodiversity informatics, and science policy. The strong quantitative and computational training also opens opportunities in data science, biotechnology and industry roles that require modeling and large-scale data analysis.

Why study at University of Michigan

The University of Michigan offers an interdisciplinary environment with extensive research infrastructure and natural laboratories. Students benefit from access to long-term field sites and facilities such as the University of Michigan Biological Station, the Museum of Zoology and botanical collections, as well as on-campus resources for genomics, microscopy and high-performance computing.

The departmental culture emphasises collaborative research across ecology, evolution, systematics and population biology, enabling students to work with investigators in complementary fields such as conservation science, bioinformatics and climate science. Graduate students receive mentorship, teaching experience and professional development support to prepare for diverse careers. Ann Arbor provides a vibrant intellectual community with proximity to field sites in the Great Lakes region, facilitating both field- and lab-based research opportunities.