Applications are invited for a full-time postdoctoral associate position in Biostatistics in the School of Public Health, University of Minnesota, Minneapolis, MN. For more information about the Biostatistics division, visit www.sph.umn.edu/academics/divisions/biostatistics/. Given the COVID-19 pandemic, remote work may be possible for this position.
The post-doc will be formally mentored by Dr. Sandra Safo (www.sandraesafo.com) and will work with Dr. Safo and her collaborators within and outside the University of Minnesota. The research will focus on developing and implementing statistical and machine learning methods for integrating high-dimensional and/or functional data from multiple sources. Possible domains of applications include cardiovascular diseases, chronic obstructive pulmonary disease (COPD), COVID-19, and HIV. Other additional duties will include: software development (R, Matlab, or in Python/TensorFlow/Keras/PyTorch for deep learning); simulation studies; real data analysis, and writing manuscripts. If the post-doc associate is interested in gaining experience in grant-writing and in competing for an extramural grant, there will be an opportunity for that.
This appointment is for 1-2 years, contingent on satisfactory performance and funding availability. Travel stipend to attend a national conference each year will be made available. The associate will be eligible for benefits that include paid and unpaid leaves of absence, and University Medical Insurance. For more, visit policy.umn.edu/hr/postdocappoint.
Starting Date: Negotiable. Position will remain open until filled.
Salary range: $56,000-$60,000 annually
The University of Minnesota offers a comprehensive benefits package for Postdoctoral Associates. For more information regarding benefits specific to Postdoctoral Associates: policy.umn.edu/media/32/download
Qualifications: A PhD degree in Biostatistics, Statistics, Computer Science or a related field, strong computing/programming and communication skills, and strong interest in omics and deep learning is required. Experience in high-dimensional data analysis, functional data analysis or deep learning is highly preferred.
How to Apply: Send an email with your CV and a cover letter outlining your research interests to email@example.com. We can chat about this position at JSM if you are interested.