Postdoctoral Fellowship in Genomics and Computational Biology


Icahn School of Medicine at Mount Sinai


New York, New York

Principal Investigator

Towfique Raj


Please send a CV and the names of at least two references to Towfique Raj (


The Raj laboratory invites applications for a postdoctoral position at the Ronald M. Loeb Center for Alzheimer’s Disease, Departments of Neuroscience, Genetics, and Genomic Sciences at the Icahn School of Medicine at Mount Sinai in New York. The lab focuses on using advanced genomic and computational approaches to identify novel drivers of neurodegenerative disease pathogenesis. The computational part of the lab has the following ongoing projects: 1) improving the computational approaches for identification of alternative splicing using short and long-read RNA-seq; (2) developing methods for detecting regulation of gene expression in bulk and single cell RNA-seq datasets; 3) developing statistical methods for integrating multi-omics data (including transcriptomics, epigenomics, proteomics, etc.); 4) developing machine learning methods that identify splicing regulatory networks controlling cell type- or condition-specific gene expression.

The successful candidate will join a highly productive multidisciplinary research team that includes geneticists, computational biologists, neuroscientists, and physician-scientists at the Ronald M. Loeb Center for Alzheimer’s. The successful candidates will play a critical role in contributing to the design and execution of the overall aims of the project.


  • Ph.D in bioinformatics, computational biology, computer science, applied mathematics or other related field.
  • Track record of publications in bioinformatics, computational biology, genomics, or systems biology.
  • Strong programming skills in Python, Perl, Java, C++ or other language.
  • Familiarity with data analysis and visualization using R.
  • Experience with Linux and high-performance computing environments.
  • Demonstrated ability in developing novel statistical or machine learning methods in computational biology.
  • Experience in genome scale data analysis such as analysis of ChIP-Seq, ATAQ-Seq, RNA-Seq data, network analysis, biological sequence analysis, or other relevant computational genomics experience.
  • Highly motivated for interdisciplinary research, excellent communication skills, and the ability to work independently as well as within a research group.