美国弗吉尼亚大学冠状动脉疾病的遗传基础方向博士后

Job Description

The Miller Laboratory at the University of Virginia seeks a highly motivated and talented postdoctoral research associate with a background in bioinformatics or computer science to investigate the genetic basis of coronary artery disease (and other related diseases). This project will focus on the integration of large-scale human genetic and multi-omic datasets (e.g. bulk and single-cell RNA-seq, ATAC-seq) from normal and diseased environments. Ultimately the goals of this work are: 1) to elucidate novel disease associated loci and regulatory profiles, 2) to map context-specific gene-gene and gene-environment interactions, and 3) to construct and test causal regulatory networks. The candidate will also be encouraged to work with collaborators to assist in building bioinformatics software and infrastructure around these genomic datasets. 

The candidate will have access to a broad range of large-scale genetic and genomic datasets and will be exposed to a stimulating and multi-disciplinary environment in the Center for Public Health Genomics (CPHG). This work will involve close collaborations with members of the CPHG and the newly formed Data Science Institute. The candidate will also benefit from strong collaborations with faculty members of the Robert M. Berne Cardiovascular Research Center and in the Departments of Biomedical Engineering and Biochemistry and Molecular Genetics. 

Candidates must have a PhD in bioinformatics, computer science, genetics or related field required in hand by appointment start date. Expertise in a quantitative field involving computational analysis is expected. The successful candidate will have knowledge of human genetics, statistical genetics and molecular biology, as well as proficiency in scripting (e.g. python, C/C++, Bash) and data analysis (e.g. R). Excellent written and verbal communication skills required. Proficiency in database language (e.g. SQL, Reddis, Mongo) is preferred, as is proficiency in machine learning, deep learning or artificial intelligence.