The University of Wisconsin-Madison (UW-Madison), United States, is recruiting PhD students in Statistical Genetics and Genetic Epidemiology for Fall 2027 through its Epidemiology and Biomedical Data Science doctoral programs. These research-focused opportunities offer guaranteed funding for at least four years, interdisciplinary mentorship, and opportunities to investigate the genetic basis of human diseases using statistical methods, large-scale biobanks, and multi-omic data. Applicants with strong research experience in statistics, biostatistics, epidemiology, human genetics, or related disciplines are encouraged to apply.
Important Dates / Deadline
- Application Deadline: November 14, 2026 (Standardized deadline set 15 calendar days after the current date because the source does not specify an application deadline.)
- Expected Enrollment: Fall 2027
Organization
- Institution: University of Wisconsin-Madison (UW-Madison)
- Department: Department of Population Health Sciences
- PhD Programs:
- Epidemiology, PhD
- Biomedical Data Science, PhD
- Academic Consortium: Interdisciplinary Biological and Health Sciences Consortium (IBHSC)
- Research Areas: Statistical Genetics, Genetic Epidemiology, Risk Prediction, and Causal Inference
Location / Study Destination
United States, Madison, Wisconsin, at the University of Wisconsin-Madison.
Who Can Apply
Applicants should meet the following eligibility criteria:
- Hold a Bachelor of Science (BSc) or Master of Science (MSc) degree by enrollment.
- Have an academic background in statistics, biostatistics, epidemiology, human genetics, or a related field.
- Demonstrate strong, focused research experience beyond coursework or course-based projects.
- Have a clear interest in statistical genetics, genetic epidemiology, or related methodological research.
- Be interested in interdisciplinary research connecting statistical methods, human genetics, and human health.
Research publications are not required.
Key Benefits / Salary / Funding
Selected PhD students will receive:
- Guaranteed Funding: Financial support for at least four years, backed by federal and institutional grants.
- Research Mentorship: Close supervision in developing research questions, selecting statistical methods, interpreting findings, and communicating research results.
- Research Independence: Opportunities to develop original research questions and lead projects from conception through publication.
- International Collaboration: Opportunities to work with researchers in the United States, Canada, United Kingdom, Australia, and other countries.
- Interdisciplinary Training: Access to expertise in statistics, epidemiology, human genetics, clinical medicine, computer science, and biomedical informatics.
- Professional Development: Opportunities to build an international research network and develop independent scientific judgment.
Main Requirements
Applicants must demonstrate strong research preparation and an interest in developing or applying statistical methods to investigate human health and disease.
Research Focus
Potential research topics include:
- Statistical genetics and genetic epidemiology
- Genetic risk prediction
- Causal inference methods
- Large-scale biobank analysis
- Multi-omic data integration
- Statistical methodology development
- Cardiometabolic diseases
- Neurodegenerative diseases
- Psychiatric disorders
- Autoimmune diseases
Epidemiology PhD Program
The Epidemiology PhD program provides research-oriented training in:
- Epidemiological study design and methodology
- Statistical methods for population health research
- Disease distribution and determinants
- Genetic, environmental, and behavioral risk factors
- Observational and experimental research
- Public health and disease prevention
Students may develop individualized research plans in consultation with their major professors.
Biomedical Data Science PhD Program
The Biomedical Data Science PhD program emphasizes:
- Statistical analysis of biomedical data
- Programming and data management
- Machine learning
- High-dimensional and heterogeneous data analysis
- Biostatistics and biomedical informatics
- Interdisciplinary research collaboration
The program includes cross-training in computer science and biostatistics, along with research rotations involving faculty mentors and scientific collaborators.
How to Apply
Interested applicants should complete the following steps:
- Select a PhD Program: Review the program information and determine which doctoral pathway best aligns with your academic background and research interests.
- Epidemiology PhD: https://lnkd.in/gP3ACZXR
- Biomedical Data Science PhD: https://lnkd.in/gjgsaiHK
- Prepare Your Research Statement: Write a brief description explaining your previous research contributions, current research interests, and fit with the research group.
- Identify a Specific Research Question: Describe a scientific question or methodological challenge in statistical genetics or genetic epidemiology that you would like to investigate.
- Contact the Recruiting Faculty Member: Send your CV and research description to: Email: tianyuan.lu@wisc.edu
- Explore Previous Research: Review recent publications to better understand the research group’s methodological approaches and potential projects.
Documents Needed
Prospective applicants should prepare:
- Curriculum Vitae (CV): Highlight academic qualifications, research experience, technical skills, and relevant research contributions.
- Brief Research Description: Summarize previous research contributions, current interests, and alignment with the laboratory’s research.
- Specific Research Question or Methodological Interest: Identify a concrete problem in statistical genetics or genetic epidemiology that you would like to explore.
A full research proposal is not required for the initial email inquiry.
Important Notes
- Recruitment is for Fall 2027 enrollment.
- Applicants can pursue doctoral training through either the Epidemiology or Biomedical Data Science program.
- Strong, focused research experience beyond course projects is required.
- Previous research publications are not mandatory.
- Applicants should demonstrate specific scientific interests rather than only expressing general enthusiasm for artificial intelligence or machine learning.
- Students will have opportunities to shape research questions and lead research projects toward publication.
- Both doctoral programs are members of the Interdisciplinary Biological and Health Sciences Consortium (IBHSC).
- The research environment emphasizes interdisciplinary collaboration, scientific independence, and international research partnerships.
