The School of Public Health Division of Biostatistics and Health Data Science (BHDS) is seeking a Post-doctoral Associate (9546, Post-doctoral Associate) to work with Dr. Thierry Chekouo and his collaborators within and outside the University of Minnesota.
The School of Public Health (SPH) is committed to antiracism and anti-oppression and welcomes you to join us in our pursuit of building equity and driving justice. We particularly encourage applications from those who belong to groups that have been historically underrepresented in our School, including those who are American Indian, Black, Indigenous, and people of color, those with disabilities, veterans, and those from 2SLGBTQIA+ communities.
Work Arrangements: The University of Minnesota endorses a "Work. With Flexibility." and we offer a flexible work environment that meets the needs of our students, faculty, staff, and partners we serve. This position has the option to work hybrid. Work arrangements will be discussed during the interview. Onsite location: 2221 University Ave. SE, Minneapolis TC Campus - East-bank.
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, contingent 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: $61,008
- Postdoc 1 year of Experience: $61,428
- Postdoc 2 years of Experience: $61,884
Questions? For preliminary inquiries, you may send your CV to tchekouo@umn.edu
Required Qualifications:
- PhD degree in biostatistics, statistics, or a related field
- Strong computing/programming and communication skills
- Strong interest in omics and/or imaging data analysis
- Demonstrated commitment to promoting a diverse, inclusive, and respectful workplace
Preferred Qualifications:
- Experience in Bayesian high-dimensional data analysis
Please note: At this time, the University's employment site is limited in how it collects applicant demographic information. Applicants are encouraged to provide their pronouns and/or preferred name within their attached application materials.
Applications must be submitted online. To be considered for this position, please click the Apply button and follow the instructions. You will be given the opportunity to complete an online application for the position and attach the following documents:
- Cover letter
- Curriculum vitae
- Graduate transcripts
- Contact information of at least two referees
To request an accommodation during the application process, please e-mail employ@umn.edu or call (612) 624-8647.
The University recognizes and values the importance of diversity and inclusion in enriching the employment experience of its employees and in supporting the academic mission. The University is committed to attracting and retaining employees with varying identities and backgrounds.
The University of Minnesota provides equal access to and opportunity in its programs, facilities, and employment without regard to race, color, creed, religion, national origin, gender, age, marital status, disability, public assistance status, veteran status, sexual orientation, gender identity, or gender expression. To learn more about diversity at the U: http://diversity.umn.edu
Any offer of employment is contingent upon the successful completion of a background check. Our presumption is that prospective employees are eligible to work here. Criminal convictions do not automatically disqualify finalists from employment.
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