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Principal Scientist, Computational Biology

Flynn Life Sciences Group, Inc.
Boston, Massachusetts, US
Closing date
Dec 9, 2021

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  • Lead cross-functional project teams and scientific working groups, and align project and team objectives with company strategy
  • Collaborate with internal and external partners in interdisciplinary teams and represent Data Science as the prime technical and/or scientific expert
  • Clearly communicate project plans, results, caveats, and rationale for decision-making with a variety of audiences including clinicians, bench scientists, industry executives, and academic researchers
  • Develop and maintain expert knowledge of advanced concepts in one or more relevant areas: microbial/host genomics, statistics, immunology, drug development and translational research
  • Propose new biological hypotheses for microbial drivers of pathology and therapy based on analysis of high throughput data, literature review, and in house experiments; work with bench scientists to design microbial and host function and phenotype experiments, and lead analysis of resulting data to test these hypotheses
  • Contribute to advancing Finch's computational platform by developing new analysis strategies for large heterogenous biological datasets (e.g. transriptomic, metagenomic, metabolomic, proteomic) through effective use of machine learning and multivariable statistics
  • Work with clinicians to analyze high-throughput trial data to enable translational research
  • May manage other computational scientists and bioinformatics research associates
  • Work effectively as part of a multifunctional team in support of a commercially viable therapeutics discovery platform

  • PhD in computational biology or a related field with 5+ years of industry experience or significant relevant post-doctoral experience in drug discovery or biomedical/clinical research
  • Track record of leading cross-functional, project-focused, teams to drive scientific discovery
  • Proven expertise in statistical analysis of high-throughput datasets from one or more of: genomics/ transcriptomics of microbial community or host systems, metabolomics, immunology, and genetics.
  • Proficiency in algorithm design, implementation and deployment using R/Bioconductor, Python, or other contemporary, open-source tools
  • Proficiency with data visualization, especially with R or python matplotlib
  • Familiarity with cloud computing, in particular Google Cloud
  • Ability to work independently
  • Eagerness to work collaboratively in a team and to both give and receive feedback to support professional development for self and others
  • Ability to perform complex analyses in a time sensitive fashion
  • Strong organizational and communications and team-work skills
  • Passion, humility, and excitement to drive research forward
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