Icahn School of Medicine at Mount Sinai Department of Genetics and Genomic Science and Columbia University in New York City invite applications for a senior research scientist position to perform computational biology/bioinformatics research on human healthy aging. This position is jointly sponsored by Drs. Tu (ISMMS) and Suh’s groups (Columbia) to work on collaborative projects to use big-data and Artificial Intelligence approach to address unmet scientific questions in human healthy aging, longevity and age-related diseases. The two groups work closely on developing computational methods to best leverage the large-scale emerging biomedical data generated at Mount Sinai/Columbia and existed in the public domain and using state-of-the-art experimental approaches to validate and further investigate the mechanisms of the findings derived from computational inference. The ultimate goal is to better understand human aging and its link to age-related diseases and eventually find novel interventions to extend human healthspan. The position offers highly competitive compensation commensurate with experience and will also enable the candidate to continue to build his/her academic record for career development.
• Design and develop computational analytical pipelines to work on big genomic/genetic data to gain novel insights and derive testable hypothesis in the field of human aging, longevity and age-related diseases
• Drive and/or participate in the preparation of manuscripts, grants, and presentations.
• Ph.D. in computational biology, bioinformatics, computer science, math/statistics, or other related quantitative discipline.
• Ideal candidate should have 1-3 years postdoctoral training working on analyzing biological omics data
• Outstanding fresh Ph.D. will also be considered
• Team oriented with abilities to think creatively and work independently.
• Excellent written and verbal communication skills with good publication record.
• Fluent in at least one and be familiar with several programming/scripting languages such as R, Matlab, Python/Jupyter, Perl, Unix.
• Previous training in machine learning, statistical modeling, deep learning, and NGS genomic analysis is a big plus.
• Some exposure to basic molecular biology and human genetics is a plus.
Interested candidates should submit CV and names with contact information of three referees to Dr. Zhidong Tu ( zhidong.tu@mssm dot edu).