Computational Biologist - Scientist I, Translational Analytics

  • Cambridge, MA
  • Full-time
  • Department: Research & Development
  • Region: US

Job Description

About This Role

The Translational Analytics group at Biogen is in search of a talented and motivated computational biologist who has expertise in RNA-seq data analysis, focusing on splice isoform analysis and single-cell ‘omics. Investigating RNA can greatly expand the druggable targets to cure disease. This requires identification of quality targets, splicing event to be modulated, and the method of modulation. The candidate will work closely with biologists and chemists to achieve this goal.

What You Will Do

  • Perform local splice variant analysis from short-read sequencing data to characterize the effect of small molecules on splicing
  • Perform splice-isoform analysis from long-read sequencing data.
  • Develop analysis pipelines for novel experimental methods to characterize splice variants.
  • Identify novel therapeutic targets that can be perturbed by modulating splicing of the RNA.
  • Support programs with internal and external ‘omics data, including single-cell RNA-seq

Who You Are

You have deep expertise in your field, and you enjoy collaborating with other experts with different background to achieve a common goal. You have scientific curiosity and knowledge to investigate new methods, which you can evaluate and modify independently. You can pay attention to details that matters, while not losing the big picture. You have excellent interpersonal and communication skills and thrive in a highly collaborative and dynamic environment. 



Required Skills

  • PhD in bioinformatics, computational biology, systems biology, or in related fields.
  • Expertise in bulk- and single-cell/nucleus RNA-seq data analysis
  • Expertise in RNA splice isoform analysis, both in short-read (e.g., Illumina) and in long-read (e.g. PacBio) platforms.
  • Experience in ingesting and adapting published analysis pipelines for internal use.
  • Proficient in R, Python, and use of HPC clusters, in the context of computational biology
  • Demonstrated ability to work independently by designing, executing, and troubleshooting given tasks

Preferred Skills

  • Expertise in deep learning and latent space interpolation, using GAN and/or AE.
  • Expertise in multi-modal ‘omics data integration.



Additional Information

Biogen is seeking a talented and motivated computational biologist who has expertise in deep learning and RNA-seq data analysis to join our Translational Analytics group in Cambridge, Massachusetts.  Excellent verbal, written communication, and presentation skills.

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