Scientist – Computational Biologist / Bioinformatician

Posted on April 29,

Orna is a Cambridge-based biotechnology startup on a mission to create therapies for diseases inaccessible to existing approaches. Built on novel circular RNA technology developed at MIT, Orna is leading the next wave of RNA therapeutics with our best-in-class expression and delivery platform. We are seeking an exceptional Computational Biologist or Bioinformatician to join our team as a Scientist to advance our high throughput discovery platform. The ideal candidate has a PhD in a bioinformatics-related field and would bring expertise in NGS data analysis and computational approaches for gaining insight into high-throughput molecular engineering strategies. They should possess strong oral and written communication capabilities, demonstrate excellent collaboration and interpersonal skills, and be adept at problem solving in a fast-paced environment.


  • Work closely with biologists, bioengineers, and bioinformatics to develop tools that advance our therapeutic platform and programs.
  • Design, implement, and evaluate novel tools to expand our high-throughput screening systems.
  • Optimize existing data analysis methods, enhancing their capabilities and technical robustness.
  • Process, analyze, and interpret high dimensional sequencing data. Extract features of interest from data relating to specific biological questions.
  • Develop and maintain version-controlled code base.
  • Effectively communicate technical information to both technical and non-technical collaborators. Identify core challenges, evaluate tradeoffs, and incorporate feedback to make decisions.
  • Prepare project timetables, schedules and deliverables.
  • Foster a driven, fast-paced, dynamic, and fun environment for rigorous science.


  • PhD in Bioinformatics, Biostatistics, Computational Biology, Genomics, or related field.
  • Minimum of 3 years’ research experience in analyzing next generation sequencing data for genomics or other applications and data visualizations.
  • Experience in Python/R programming, unix command line, bioinformatic toolkits, and version control systems (e.g. git).
  • Experience writing and maintaining end-to-end analysis pipelines with workflow management tools (e.g. Snakemake, Nextflow).
  • Strong scientific understanding of RNA molecular biology and genomics. Work experience with data from SHAPE-Map, Clip-Seq, Ribo-seq, CRISPR library screenings, SNP callings etc.
  • Experience with Nanopore technology and/or machine learning algorithms is preferred.
  • Demonstrated quantitative and scientific thinking as evidenced by a strong publication record.
  • Goal-oriented and organized with excellent project management skills. Can collaborate on execution of multiple, parallel studies with internal and external partners. Able to prioritize and complete tasks in a timely manner.
  • Hands-on experience using Amazon Web Services is preferred.