Job ID: 375759
About the Job
The School of Public Health Division of Biostatistics and Health Data Science (BHDS) is seeking applications for a Post-Doctoral Associate (9546 Post-Doctoral Associate) position. For more info on the division, visit http://www.sph.umn.edu/academics/divisions/biostatistics/.
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.
Duration: This appointment is for 1-2 years, with a possible extension to year 3 depending on satisfactory performance and funding availability.
Starting Date: Negotiable. Position will remain open until filled.
Annual Salary: Based on NIH NRSA postdoctoral stipend levels.
Onsite location: University Office Plaza, 2221 University Ave SE, Minneapolis, Twin Cities Campus - East-bank.
Sponsorship: This position is not eligible for H-1B visa sponsorship.
Qualifications
Qualifications
About the Job
The School of Public Health Division of Biostatistics and Health Data Science (BHDS) is seeking applications for a Post-Doctoral Associate (9546 Post-Doctoral Associate) position. For more info on the division, visit http://www.sph.umn.edu/academics/divisions/biostatistics/.
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.
Duration: This appointment is for 1-2 years, with a possible extension to year 3 depending on satisfactory performance and funding availability.
Starting Date: Negotiable. Position will remain open until filled.
Annual Salary: Based on NIH NRSA postdoctoral stipend levels.
- Postdoc No Experience: $63,480
- Postdoc 1 year of Experience: $63,900
- Postdoc 2 years of Experience: $64,380
Onsite location: University Office Plaza, 2221 University Ave SE, Minneapolis, Twin Cities Campus - East-bank.
Sponsorship: This position is not eligible for H-1B visa sponsorship.
Qualifications
Qualifications
- Required 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.