The School of Public Health is committed to anti-racism and anti-oppression in our mission and operations. In pursuit of this goal, we consider an applicant’s record working with individuals from historically marginalized backgrounds, and experience identifying and eliminating systemic barriers to success in an academic environment. SPH seeks to increase the diversity of its workforce, we particularly encourage applications from those who belong to groups that have been historically underrepresented in our discipline, including those who are Black, Indigenous, and people of color, those with disabilities, and those from LGBTQIA+ communities.
Applications are invited for a postdoctoral associate position in Biostatistics in the School of Public Health, Division of Biostatistics, University of Minnesota, Minneapolis, MN. The successful candidate will work with Dr. Thierry Chekouo and his collaborators within and outside the University of Minnesota. The research will focus on the development of Bayesian statistical/machine learning methods for the data integration analysis of high-throughput imaging and molecular data (i.e., genome, transcriptome, epigenome, and more). The methods would be able to systematically integrate biomedical/biological knowledge to improve the prediction power of clinical outcomes. Domains of applications may include cancer and cardiovascular diseases, and neurodevelopment disorders. The post-doc will also work on software development (in R, or in Python, Java, Stan, or BUGS or interfacing R with C/C++), simulation studies, real data analysis, and writing manuscripts.
This appointment is for 1-2 years, with a possible extension to year 3, contingent on satisfactory performance and funding availability.
Starting Date: Negotiable. Position will remain open until filled.
Questions? For preliminary inquiries, you may send your CV to firstname.lastname@example.org
Qualifications: A PhD degree in Biostatistics, Statistics, or a related field, strong computing/programming and communication skills, and a strong interest in omics and/or imaging data analysis are required. Experience in Bayesian high-dimensional data analysis is highly preferred.
The University of Minnesota, founded in the belief that all people are enriched by understanding, is dedicated to the advancement of learning and the search for truth; to the sharing of this knowledge through education for a diverse community; and to the application of this knowledge to benefit the people of the state, the nation, and the world.