The Skok lab (http://www.tsirigos.com/) at the NYU School of Medicine is seeking a highly motivated, enthusiastic and creative individual to investigate the role of genetics, epigenetics and chromatin organization in cancer and/or apply machine learning to develop novel cancer diagnostics. The successful candidate will have the opportunity to work on various types of large genomics datasets and will interact closely with wet and dry Skok lab members. The successful candidate will also interact with a vibrant group of bioinformaticians in the Applied Bioinformatics Laboratories (http://labs.pathology.med.nyu.edu/skok-lab/). 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.
· 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 (e.g. DNA-seq, RNA-seq, ATAC-seq or ChIP-seq)
· 3+ years of experience creating customized sequencing analysis pipelines
· Excellent communication skills with proficiency in written and oral English
· 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