Scientist, Bioinformatics

Location: Cambridge, MA


We want to cure cancer by targeting its core transcriptional mechanisms and programs with novel small molecule drugs. You will help build a platform that can elucidate oncogenic transcriptional networks and mechanisms of action for novel small molecule therapies against historically undruggable oncology targets from multi-omics datasets. You will manage, integrate, analyze, and visualize multi-omics data and workflows to characterize chemical and genetic perturbations of tumors to infer relevant regulatory networks.

You have a results-oriented mindset, paired with an eagerness for learning, and willingness to contribute to a strong culture of teamwork and collaboration in a fast-paced environment.


  • Develop, evaluate, implement, and perform algorithms and reproducible workflows for data analysis
  • Work closely with the target validation team and contribute to the identification and validation of novel oncology targets leveraging public and proprietary datasets
  • Empower Biology and Chemical Biology teams to develop, optimize and implement experimental and analytical strategies
  • Identify or validate target engagement, mechanism of action and biomarkers for sensitivity to novel anti-cancer therapies, leveraging and integrating public and proprietary datasets
  • Communicate and visualize results clearly and succinctly in plots and dashboards
  • Summarize and present scientific results with clear conclusions and recommendations
  • Develop documentation of analyses conducted and/or analysis plans and specifications, as appropriate.
  • Support infrastructure and provide code base maintenance (documentation, testing, and version control)
  • Maintain expertise in state-of-the-art computational methods


  • MSc or PhD in Bioinformatics, Computational Biology, Computer Science, or related discipline with 2+ years of hands-on experience
  • Proficiency in data analysis including several of the following: Diverse types of genomics data such as RNA-Seq, ChIP-Seq, and ATAC-Seq, CRISPR screening, scRNA-Seq
  • At least basic understanding of statistical analysis principles
  • Facility in Python (SciPy, NumPy, Pandas) and/or R (Tidyverse), as well as statistical data analysis and visualization tools/packages (e.g. Shiny, Plotly, Matplotlib)
  • linux/unix based environments, version control (GitHub), Docker
  • Familiarity with public data resources like DepMap, CCLE, TCGA or others
  • Familiarity with data visualization tools and the ability to present complex datasets and analyses to cross-functional audiences
  • Training and experience in supervised machine learning techniques a plus
  • Experience with AWS (e.g. SageMaker) a plus
  • Experience with workflow management (Snakemake, Hail, Nextflow) a plus
  • Experience with scRNA-Seq datasets a plus
  • Embodies Kronos values; exhibits high degree of integrity and professionalism when interacting with outside investigators and vendors
  • Entrepreneurial and enjoys working in a fast-paced, creative and resourceful small company environment

To apply for this position, please forward your resume and cover letter to