Bioinformatics Analyst

NYU Langone Medical Center
New York City, New York (US)
Commensurate with experience
December 03 2018
Position Type
Full Time
Organization Type

The Endocrine Division and Diabetes Research Program of the Department of Medicine at NYU School of Medicine are seeking a highly motivated, enthusiastic and creative individual to become part of a team of scientists that investigates the genomic and epigenetic mechanisms of diabetes, obesity and cardiovascular disease using computational approaches.  The successful candidate will have the opportunity to work on various types of large datasets generated from next-generation sequencing methods including single-cell approaches and will interact with our experimental collaborators.

The projects are focused on the metabolic, transcriptomic, and epigenetic characteristics of inflammatory cells called macrophages as well as other immune cells, in sites that become dysfunctional in the major health problems, in diabetes/obesity (fat, heart and vascular systems).

Besides the Program scientists, the successful candidate will also interact with a vibrant group of bioinformaticians in the Applied Bioinformatics Laboratories ( at the School. ABL provides computational support and expertise to promote innovative cutting-edge research conducted by principal investigators at the NYU Langone Medical Center.

This is a great opportunity to quickly acquire new skills, develop and publish new tools and methods, analyze challenging datasets and be a co-author in multiple studies on diseases with major impacts on mortality and morbidity world-wide.


  • Work closely with bench scientists to understand and help accomplish their research goals
  • Analyze various types of sequencing data analysis (e.g. RNA-seq, ChIP-seq, ATAC-seq, Hi-C-seq, bisulfite sequencing, whole-genome sequencing)
  • Perform robust data quality control and validation
  • Adapt genomic data analysis pipelines in a rapidly evolving research environment
  • Develop novel methods for multi-omics data analysis and integration, including machine learning

Required skills

  • Ph.D. or M.Sc. in Bioinformatics, System Biology, Computer Science or related field
  • Knowledge of biology and understanding of key and complex biological concepts (genes, pathways, cancer and/or stem cells)
  • Ability to work independently while collaborating and assisting the team in its common research goals
  • Attention to detail and ability to work on multiple projects is necessary
  • Experience in Unix/Linux systems including HPC environments
  • Scripting languages: Python (preferred) or Perl
  • Statistical packages: R (preferred) or Matlab
  • 3+ years of experience with sequencing data (two of DNA-seq, RNA-seq and ChIP-seq)
  • Experience creating customized sequencing analysis pipelines, including incorporating machine learning approaches
  • Excellent communication skills with proficiency in written and oral English

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