Research Fellow position in bioinformatics and genomics supported by T32 training grant
How to Apply
Interested individuals should submit their (1) CVs; (2) evidence of programming skills; and (3) three reference letters. Send all application materials to Dr. Alex Lam C Tsoi and Dr. James T Elder via email: (alextsoi@med.umich.edu and jelder@med.umich.edu).
Job Summary
A research fellow position is available for individual interested in conducting systems biology researches and analyzing high dimensional data to study complex skin diseases in the University of Michigan (U-M) Medical School. We are interested in the genomic basis of complex skin diseases and we have access to unique genetic, transcriptomic, epigenetic, single cell genomics, and clinical data. U-M is a world renowned research university, and our group is highly collaborative and work with top investigators in Dermatology, Statistical Genetics, and Computational Medicine. The person hired will be developing novel biomedical informatic methods to analyze health record data and integrating results with different high dimensional genomics data available.
The University of Michigan at Ann Arbor provides excellent training environment for researchers and very attractive benefits packages to the employees. Ann Arbor is among the most educated cities in US and is often ranked as one of the best places to live.
Required Qualifications
Candidates should: (1) be US citizens/permanent residents; (2) have PhD in computer science, biomedical informatics, statistics, computational biology, or a related field within the last 3 years; (3) have strong programming skills in traditional programming or scripting languages; (4) have strong interest in conducting biomedical research and designing innovative analysis pipeline to study high dimensional data; and (5) possess strong communication and writing skills.
Desired Qualifications
Prior experience in conducting research in analyzing medical health records is a strong plus. Research experience in processing/analyzing genomic data is preferred but not required.