Mount Sinai Careers


New York, New York
Allied Health

Job Description

Computational Genomics Postdoctoral Fellow
The Raj Laboratory at Icahn School of Medicine at Mount Sinai is seeking a computational postdoctoral fellow. The qualified candidate should be highly motivated, with experience in human genomics, computational biology, RNA biology, neuroscience, or a related field. He or she should have experience analyzing genomic and transcriptomic datasets derived from high-throughput sequencing technologies. Experience with RNA-Sequencing tools and methods are a big plus. A good understanding of genetics is required. Because the work involves multiple collaborators, a good balance between independence and team spirit is essential, and effective communication skills are necessary. Candidates are required to have a Ph.D. degree. This position is mentored by Dr. Raj working under the broader leadership of Drs. Alison Goate, Eric Schadt, and Eric Nestler.
1. Candidates should have a Ph.D., M.D. or equivalent doctorate in a quantitative field such as statistical genetics, biostatistics, bioinformatics, computer science, or a related discipline.
2. Candidates should have proficiency in programming (e.g. Perl, Python or C/C++) and statistical computing (e.g. R).
3. Candidates should have a track record of scientific productivity and/or leadership.
The Raj Laboratory is a member of the Ronald M. Loeb Center for Alzheimer's Disease, Departments of Neuroscience, Genetics, and Genomic Sciences, Institute for Genomics and Multiscale Biology, and Friedman Brain Institute at Icahn School of Medicine at Mount Sinai. The research in the Raj lab focuses on mechanisms underlying the regulation of gene expression and how these mechanisms are disrupted in neurodegenerative diseases. More info:
The Institute for Genomics and Multiscale Biology at the Icahn School of Medicine at Mount Sinai seeks to comprehensively integrate the digital universe of information into research, training, and patient care and to develop programs that prepare students for careers in the future of healthcare and data science.