Decibel is seeking a Subject Matter Expert within Human Genetics, reporting to the Director of Computational Biology, to help drive collection and analysis of data around the genetics of hearing function, hearing loss, and genetic deafness. Responsibilities will include:
Design, conduct, and analyze human genetics studies to help drive drug discovery and development.
Identify and develop relationships with appropriate external partners.
Develop sample collection and genotyping strategy.
Work with translational sciences group to develop cohort selection and phenotyping strategies.
Develop and implement computational analysis strategy with appropriate statistical rigor.
Help develop a robust platform for human genetics data storage and access.
Help guide genomics platform efforts at Decibel, including genetic screening, single-cell RNAseq, and other data types.
Apply and/or develop data-mining techniques for target identification.
Apply machine learning and statistical approaches to establish and benchmark predictive models of disease.
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 statistical and population genetics. Understanding of hearing biology is a plus.
Experience in human genetic analysis and its application to practical problems.
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
Excellent written and verbal communication skills, particularly of complex information and concepts.