Postdoctoral fellow in cell- and tissue-level transcriptional profiling of craniofacial development

Bakel lab
Approximately $55,000 (NIH pay scale)
February 09 2018
Position Type
Full Time
Organization Type
Job Type

Craniofacial sutures are the fibrous joints between bones, allowing growth of the skull from prenatal to postnatal development until adult size is achieved. Craniosynostosis, the premature fusion of skull sutures, is a common birth defect, occurring in 1/2500 live births. As part of the FaceBase consortium we have performed extensive single-cell and tissue-level transcriptional profiling of distinct subregions of craniofacial sutures in mouse at different embryonic stages, to gain a more comprehensive understanding of suture biology and pathology. The Bakel, Holmes, and Jabs labs are now looking for a Postdoctoral Fellow with a bioinformatics or computer science background to use these data to map the regulators and biological pathways that coordinate suture development. The project involves a broad array of well-established techniques such as RNA-Seq of laser capture microdissected (LCM) tissues, but also cutting-edge single-cell sequencing technologies and other specialized approaches to study gene regulation at the cellular level. Projects in our labs are widely funded through NIH grants and contracts. Our lab websites and publication records can be found at:,, and 

The candidate will work within an integrated, multidisciplinary team of experimental and computational scientists at the Institute for Genomics and Multiscale Biology at the Icahn School of Medicine at Mount Sinai. The ideal candidate will have a Ph.D. in bioinformatics, or computer science, with a background in transcriptome analyses and excellent quantitative skills. The successful applicant will have strong training in genomic and co-expression network analyses and data mining, and the ability to work in a collaborative team setting.

Specific qualifications include experience in one or more of the following areas:

  • Genomics and RNA-Seq data analysis
  • Differential gene expression profiling (e.g., using voom/limma)
  • Co-expression network analysis (e.g., WGCNA, MEGENA)
  • 10x genomics single-cell expression analysis (e.g. Seurat)
  • Statistical analysis (e.g., using R, Matlab)
  • Programming (e.g., python, C/C++, or Java)

Additional qualifications include:

  • Ability to complete tasks efficiently and independently
  • Strong work ethic and attention to detail
  • Excellent verbal and written communication skills
  • Ability to work in a collaborative setting

The Icahn School of Medicine at Mount Sinai is an equal opportunity/affirmative action employer. We recognize the power and importance of a diverse employee population and strongly encourage applicants with various experiences and backgrounds.

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