Postdoctoral Scientist, Bioinformatics / Computational Biology

Cambridge, Massachusetts
Aug 20, 2019
Required Education
Position Type
Full time

Wave Life Sciences, USA is looking for a creative and highly motivated postdoctoral fellow to leverage their strong coding background, and their significant understanding of human genetics, bioinformatics tools, and relevant databases, to drive oligonucleotide therapeutic discovery and drug development. The successful candidate will be an integral member of the Data Science Team and work cross-functionally with biological scientists and chemists. The candidate project will focus on using in silico computational approaches to predict drug on- and off-target effects, as well as building pipelines that integrate these tools with Wave’s discovery platform. This work will influence internal guidance for the development of oligonucleotide therapeutics and impact target selection. The candidate will be encouraged to publish their key findings.

Degree & general requirements

  • Minimum Ph.D. in bioinformatics, computational biology, human genetics, or related field
  • Excellent communicator; able to prioritize, plan, summarize and explain work to collaborative teams and management
  • Curiosity and a strong ability to work independently
  • Domain expertise
  • RNA sequencing data processing and analysis; applied knowledge of statistical algorithms for differential expression and alternative splicing
  • Accessing, processing, and analysis of public expression datasets (such as GTEx, GEO, ArrayExpress) and human variation databases (such as gnomAD, dbSNP, 1000 Genomes)
  • Deep understanding of Variant Call Format (VCF) files, bioinformatic software and tools
  • Familiarity with single-cell sequencing protocols
  • Strong statistical background (classical & Bayesian techniques), machine learning

Key Responsibilities

  • Perform computational modeling and network analysis based on experimental expression data. Integrate human variation and high throughput RNA sequencing data to generate in silico toxicology insights.
  • Understand oligonucleotide cellular localization using single-cell sequencing from disease model systems
  • Predict drug mechanisms (allele-selective mRNA knockdown, exon-skipping correction, RNA editing) and off-target interactions; generate and refine models. Work closely with biologists to design screening experiments to test hypotheses,
  • Development of novel databases of biological and clinical genomics data
  • Build processes and dedicated pipelines/workflows to generate novel insights to drive the drug discovery pipeline
  • Work with software engineers to develop web-based tools for Wave's scientists to interact with and learn from the information described above: internal knowledgebases of diseases, targetable diseases, possible mechanisms & oligonucleotide strategies
  • Work cooperatively with Data Science teammates on other bioinformatic projects related to Wave's stereo-defined oligonucleotide platform

Language/tool requirements

  • Must: R & R::Bioconductor suite, SQL
  • Plus: Python, Knime