Senior Computational Scientist at Decibel Therapeutics
Boston, MA, US
The Senior Computational Scientist, reporting to the Director of Computational Biology, will work as part of cross-functional project teams to drive research focused on the elucidation of hearing biology and the discovery and development of therapeutics for hearing loss. Responsibilities will include:

Help develop a robust platform for genomics-based target discovery, including single-cell RNAseq data, population genetic data, and genetic screen data.
Apply and/or develop data-mining techniques for target identification and validation.
Apply machine learning and statistical approaches to establish and benchmark predictive models of biological data.
Help guide design of gene therapies, including computational aspects of promoter and capsid optimization.
Enhance the scientific reputation of the company through publishing and/or or presenting technical papers to internal and external audiences, and/or contributing to patent applications.
Design and develop innovative, robust, analysis pipelines that can be applied in a research and clinical setting.
Develop and contribute to external collaborations and partnerships.


M.S./Ph.D. in bioinformatics, computational biology, genetics or a related discipline.
Strong understanding of cellular and molecular biology. Understanding of hearing biology is a plus.
Expertise in computational biology, genomics and other high throughput data platforms including scRNAseq. Aptitude to apply experimental methods to understand disease biology and drug discovery.
Proficiency in programming and computational analysis. Experience with R, Python and SQL are desirable.
Ability to apply and develop tools for integrative analysis and visualization of multi-dimensional datasets, integrating biochemical, cellular and genomic data using appropriate statistical methods to drive drug discovery projects.
Ability to work effectively with internal and external collaborators to funnel emerging genomics discoveries to guide internal programs and identify partners/consultants to complement internal bioinformatics efforts.
Other ideal areas of scientific expertise:
Fundamental statistics and machine learning applications to life sciences
Predictive modeling, benchmarking
Experience with mining public data sets
Technical proficiencies should include:
Linux in a grid or cloud environment.
One or more scripting and statistical languages
Distributed computing
Excellent written and verbal communication skills, particularly of complex information and concepts.