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Bioinformatician position: RNA regulatory networks

Memorial Sloan-Kettering Cancer Center
Developmental Biology
United States NY 10065
https://www.mskcc.org/research/ski/labs/eric-lai

Description

We seek a motivated bioinformatician to be involved in our studies of post-transcriptional regulatory networks. Our laboratory at Memorial Sloan-Kettering Cancer Center combines computational and experimental approaches to discover, annotate and functionally elucidate diverse post-transcriptional regulatory pathways and their biological impacts. Currently, we are particularly interested in non-canonical small RNA pathways, alternative mRNA processing strategies, and RNA methylation. Towards these ends, we produce RNA-seq, 3'-seq, CLIP-seq, small RNA, RNA modification and ChIP-seq data, and analyze these with respect to the rich comparative genomic data available for Drosophila and mammals.

The candidate will integrate into projects that seek the mechanistic bases and impact of (1) tissue-specific alternative polyadenylation, and (2) regulation and dysregulation of miRNA biogenesis. There is a close exchange of ideas between dry and wet lab members to generate and test biologically-based hypotheses. Postdoctoral fellows are offered a generous salary and comprehensive benefits package including full medical for themselves and all dependents and subsidized housing nearby.

https://www.mskcc.org/education-training/postdoctoral/resources-postdocs/compensation-benefits-resources



Qualifications

Relevant candidates will have strong computational skills and be experienced with analyzing deep-sequencing data, comparative genomics and statistics. Fluency with at least one general purpose programming languate (e.g. Perl or Python), a language for statistical computing (e.g. R), proficiency with bash/shell scripting in LINUX/UNIX systems, and knowledge of HTML/JavaScript for building web-based data interfaces.

Excellent problem solving, independent thinking, communication skills and scientific curiosity are critical. Working knowledge (and desire to learn) how experimental datasets are generated, appreciation for biological variability, technical artifacts, and, experimental validation of computational conclusions, and teamwork between dry/wet lab are fundamental to the projects.


Start date

As soon as possible

How to Apply

Please send motivation letter including details of prior research experience, CV, and contact information of three references to laie@mskcc.org.


Contact

Eric Lai
laie@mskcc.org