Senior Computational Scientist

Job Description:
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.

• Fundamental statistics and machine learning applications to life sciences
• Predictive modeling, benchmarking
• Experience with mining public data sets

• 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.

Requeriments :

• M.Sc. or higher Degree in Bioinformatics
• M.Sc. or higher Degree in computational biology
• Master’s Degree in Genetics

Skills :

• Biology
• Cell Biology
• Computational Biology
• Data Mining
• Genetics
• genomic
• Lunix/Unix
• Machine Learning
• Modeling
• molecular biology
• Population Genetics
• Programing in Python
• Programing Skills
• Programming in R
• RNA-seq
• SQL
• Statistics

Areas :

• Other

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