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Principal/Senior Scientist, Computational Biology

Employer
Dark Horse Talent
Location
Cambridge, Massachusetts, US
Salary
Competitive
Closing date
May 17, 2022

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Sector
Consultancy/Private Sector
Field
Informatics / GIS
Discipline
Genetics, Biology
Salary Type
Salary
Employment Type
Full time
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Opportunity to lead computational genomics to support the discovery and development of novel gene-editing technologies. You will develop and implement a strategy for novel protein discovery and contribute to advancing programs for proof-of-concept studies. You will contribute scientific, technical, and leadership expertise to a multidisciplinary team, emphasizing conceptualization, experimentation, data analysis, presentation, and strategic planning.

Opportunity to:
  • Develop and utilize strategies from comparative genomics, evolutionary biology, and sequence analysis to propose and implement methodologies for novel discovery.
  • Lead the implementation of computational pipelines to mine large-scale genome sequencing data.
  • Exercise autonomy by working independently while also collaborating with an exceptional team to design, analyze, and interpret multi-omics technologies focused on discovering novel approaches to genetic treatments/therapies
  • Lead and mentor junior scientists to collectively achieve team goals.
  • Work closely with experimental scientists to ensure that data is effectively utilized for high-level impact.
  • Present scientific findings with high visibility to senior leadership to drive decision-making.

We are looking for:
  • Ph.D. in Computational Biology, Bioinformatics, Biology, Genetics, Evolutionary Biology, or related discipline.
  • NGS experience
  • Experience with strategies for genome-scale mining initiatives.
  • Ability to lead projects and mentor junior scientists

You will stand out if you have:
  • Experience with mobile genetic elements or virology
  • Experience/familiarity with gene identification, functional annotation, or comparative genomics.
  • Proficiency in handling large-scale sequencing data in a cloud environment (AWS preferred).
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