ReadCoor, Inc.


Job Locations US-MA-Cambridge
Posted Date 2 months ago(1/31/2018 10:49 AM)


At ReadCoor we are solving some of biology’s greatest unanswered questions. We have introduced the next generation of “Omics” by delivering the first panomic spatial sequencing platform to a global audience of researchers, clinicians, pharma diagnostics companies, and ultimately patients.  Our development efforts are at the intersection of biology and engineering.  We are seeking an enthusiastic and experienced bioinformatician. The candidate will be responsible for genetics informatics, including alignment and database-driven discovery.


This position focuses on analyzing RNA-seq and single cell RNA-seq (scRNA-seq) datasets, including developing novel pipelines and computational approaches for single cell RNA-seq data analyses. The ability to develop, evaluate and implement new techniques will be critical. The successful candidate is required to be very familiar with next generation sequencing (NGS) technologies and data analyses, has strong programming skills in R, Perl or Python, C++ or Java.



  • Employ and extend state-of-the-art open source tools for RNA-seq data analysis, including developing reports encompassing differential gene expression, splice variant, and expressed SNP analysis.
  • Evaluate state-of-the-art open source tools for scRNA-seq data analysis
  • Build pipelines and creating tools to manage large volumes of sequencing data and assist with generating and assessing meta-data to support internal R&D efforts.
  • Develop or extend in-house workflow to streamline NGS data analysis workflow and visualization
  • Improve computational approaches related to NGS data QC and normalization, clustering of cell populations, inferring cellular trajectories and reconstructing lineage hierarchies
  • Analyze scRNA-seq dataset generated for internal and external collaborations
  • Design and generate data reports for scientists
  • Write and publish articles in quality peer-reviewed journals, and present at internal and external meetings


  • A Ph.D. in Bioinformatics or computational biology related fields
  • Passion to build innovative software solutions and data analysis pipelines
  • Extensive knowledge in the NGS field with a demonstrated track of record in RNA-seq data analysis, including data QC, read mapping and quantification, data normalization and differential analysis
  • Experience working with single-cell RNAseq datasets
  • Familiar with NGS algorithms, such as Bowtie, BWA, STAR, cufflinks, RSEM, featureCounts and etc.
  • Must be proficient in Unix/Linux, cluster and programming with R, Perl/Python, Java or C++
  • Significant experience in algorithm development and implementing pipelines for NGS data analysis
  • Deep scientific knowledge in either immunology, oncology or neuroscience
  • Knowledge in Amazon cloud computing, Apache Hadoop and Spark, and Docker is a plus
  • Strong publication record of original scientific work in high-quality peer-reviewed journals


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