Welcome to the Center for Statistical Genetics

The Department of Biostatistics and Center for Statistical Genetics at the University of Michigan invite applications for multiple positions emphasizing the statistical design and analysis of genome-wide sequencing and association studies. Our group plays a leading role in multiple large-scale genetic studies including the Finland-United States Investigation of NIDDM Genetics (FUSION) study of type 2 diabetes, the SardiNIA study of aging-related phenotypes, and the 1000 Genomes Project. Recently funded projects focus on genome-wide association studies and large-scale resequencing for several traits and disorders. We are seeking candidates for the following positions:

• Research Assistant Professor/Assistant Research Scientist
• Post-Doctoral Fellows
• MS- or PhD-level Statistical Genetic Analysts
• Scientific Programmers

The Center for Statistical Genetics is an interdisciplinary program which seeks to encourage research and training at the interface between human genetics and the mathematical sciences. The goals of the Center for Statistical Genetics are to:

• Build an intellectual community of faculty and students
• Promote methodological research to develop useful statistical and mathematical models and methods for genetic studies
• Foster the use of innovative models and methods to address problems in genetic studies of human health and disease
• Encourage collaboration and technology transfer between academia and private industry
• Provide interdisciplinary training to students and fellows
• Generate financial support for the research and training in statistical genetics at Michigan

The human genome project is changing the practice of medicine and public health, and genetics is playing an ever more central role in all the biomedical sciences. This expanding role includes the mapping and sequencing of the human genome and the genomes of other organisms, the identification of all human genes and the cataloging of all common human genetic variants, the development of methods to assay the expression of many genes simultaneously, the investigation of the molecular evolution of human genes, and the translation of the resulting knowledge to address questions of human health and disease. These developments present remarkable opportunities for the prevention and cure of human disease, but require investigators working at the interface between human genetics and the mathematical sciences.