Computational Biologist - Data Science at Fulcrum Therapeutics
Cambridge, MA, US

We are seeking a highly motivated Computational Biologist – Data Science at the Scientist or Sr. Scientist level to join our drug discovery efforts at Fulcrum. This position will focus primarily on the analysis of transcriptomic and epigenomic NGS data generated from a panel of compound perturbations in multiple cellular contexts across multiple cell-types in conjunction with human or model organism phenotypic data as it relates to our therapeutic programs.


  • This position will focus on the development and application of statistical methods for the integrated analysis of large­scale molecular datasets.
  • Perform exploratory data analysis of very large datasets from varying sources, drawing inferences and insights to design or tune statistical models/learning algorithms for identifying genes predictive of phenotypes or clinical outcomes.
  • Evaluate fits, error metrics and model diagnostics to assess and improve model performance.
  • Perform data collection and curation.
  • Interpret analysis to a broad array of wet-lab scientists.


  • An advanced degree in a relevant technical field (i.e. Bioinformatics, Computational Biology, Statistics, Computer Science, Engineering, Physics, Math)
  • Experience with a wide array of machine learning algorithms and data mining methods (i.e. time series analysis, state space models, adaptive filtering, mixed effect models, hierarchical Bayes, Markov models, decision trees, boosting, random forests, support vector machines).
  • Experience analyzing genomics, epigenetics and transcriptomic datasets.
  • Proficient programming skills (e.g. Python, C++, Scala).
  • Expert knowledge of a statistical analysis package (e.g. R, Matlab, SAS).
  • Experience with high performance computing, preferably on a cloud platform (e.g. AWS).
  • Proficient with data visualization techniques.
  • Evidence of maturity, resourcefulness, and leadership potential.
  • Prefers team oriented, collaborative work environments.
  • Excellent oral and written communication skills, fluency in English.
  • Publications in relevant journals.