As an independent research organization, the Morgridge Institute for Research explores uncharted scientific territory to discover tomorrow’s cures. In affiliation with the University of Wisconsin-Madison, we support researchers who take a fearless approach to advancing human health in emerging fields such as regenerative biology, metabolism, virology and medical engineering. Through public programming, we work to inspire scientific curiosity in everyday life.
The Stewart Bioinformatics Group is a computational biology group focusing on developing methods for analysis of large biomedical datasets. We are recruiting post-doctoral researchers to develop novel computational data analysis tools to solve cutting-edge problems in regenerative biology. Some of the relevant data types include, but are not limited to, the following: bulk and single cell RNA-seq, ATAC-seq, ChIP-seq, large text corpora such as PubMed, and electronic health records. The specific project will depend on the candidate’s experience and interest as well as the needs of the lab. Most positions are interdisciplinary and will involve direct collaboration with University of Wisconsin-Madison faculty in the departments of Biostatistics and Medical Informatics and/or Computer Science.
Successful candidates will join an experienced, diverse, and growing multidisciplinary group focused on the goal of understanding human biology.
Candidates should have a Ph.D. in computer science, statistics, bioinformatics, computational biology, statistical genomics, or a related field and proven research productivity as demonstrated by publications. It is expected that the candidate will have experience in one or more of the following areas: gene network analysis, machine learning, natural language processing, data/text mining, single cell RNA-seq analysis, or similar. The ability to build integrative models across multiple data types is highly desired. The ideal candidate will be a highly motivated, creative person with the ability to learn quickly and function both independently and within a team and have excellent written and oral communication skills.
Qualified candidates interested in this opportunity are required to submit a single PDF document containing their CV and a cover letter detailing their current and previous research and names and addresses of three references within the career section.