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Scientist, Computational Biology

Foghorn Therapeutics
Cambridge, Massachusetts, US
Closing date
Jul 30, 2021

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Academic / Research
Informatics / GIS
Modeling, Biology
Salary Type
Employment Type
Full time
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About Foghorn

Foghorn Therapeutics is pioneering the discovery and development of a new class of medicines targeting genetically determined dependencies within the chromatin regulatory system, an untapped opportunity for therapeutic intervention. Our proprietary Gene Traffic Control® platform gives us an integrated, mechanistic understanding of how the various components of the chromatin regulatory system interact, allowing us to identify, validate and potentially drug targets within the system. The Company, currently in the clinical stage, is advancing over 10 small molecule and protein degrader programs across a wide range of cancers.

Foghorn was founded in 2016 by Cigall Kadoch, Ph.D., Gerald Crabtree, M.D., and Doug Cole, M.D., of Flagship Pioneering. Learn more about Foghorn at

About the Chromatin Regulatory System

The chromatin regulatory system regulates gene expression by directing the movement of molecules that turn genes on and off. Disease dependencies associated with the chromatin regulatory system are estimated to impact over 2.5 million cancer patients across the United States, Europe and Japan. This system is further implicated in neurological, autoimmune, and other serious diseases.

Job Summary

We are seeking a Computational Biologist to join our passionate team of scientists. You will tackle computational challenges to uncover new insights about RNA biology and the molecular underpinnings of disease. Working alongside experimentalists, you will analyze next generation sequencing data generated by our first-in-class technology platform, relating this data to publicly available datasets. Your role will also involve aspects of data management/infrastructure, computational biology, machine learning, and business strategy. Successful candidates should be scientifically motivated self-starters, comfortable working in a fast-paced entrepreneurial environment and keen on modeling biological processes using rich datasets.

Key Responsibilities
  • Create and maintain pipelines for processing high-throughput next-generation sequencing data for genomics, epigenomics, and transcriptomics studies
  • Analyze and extract biological insights from public and proprietary datasets by leveraging existing methods or developing new computational methods when needed
  • Cultivate a data-centric company philosophy by creating best practices for data sharing and management
  • Maintain scientific and technical expertise through familiarity with scientific literature, attending conferences, and developing relationships with thought leaders
  • Work closely with an entrepreneurial, highly-collaborative, interdisciplinary team and actively contribute to creating, shaping and executing the scientific and strategic vision of the company

  • PhD or equivalent experience in Bioinformatics, Computer Science, Computational Biology, Genetics, Mathematics, Statistics or a related field. Experience in cancer genetics, epigenomic research, chromatin biology, and/or transcriptional regulation highly desired
  • A strong self-starter, independent thinker, with strong attention to detail
  • Demonstrated industry experience or academic achievement
  • Excellent communication and presentation skills, capable of conveying technical information in a clear and thorough manner.
  • Confident execution focused, team-oriented with an ability to thrive in an entrepreneurial environment

Additional Qualifications of Interest
  • Understanding of biology of transcription and/or chromatin regulatory system
  • Experience with statistics or machine learning, especially as it relates to modeling biological processes using next-generation sequencing data
  • Familiarity with publicly available next-generation sequencing datasets such as TCGA, the Dependency Map, etc.
  • Programming skills in a scripting language such as Python or R
  • Proficiency in creating reproducible workflows with an emphasis on Unix, Git, Jupyter or RMarkdown, and cloud computing environments such as Amazon Web Services
  • Experience in creating dashboards or other utilities to allow biologists to investigate data independently

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