Computational Biologist Position

Day Zero Diagnostics is a machine learning based genomics start-up in Boston that is seeking to recruit a highly motivated computational biologist to join our team. At Day Zero Diagnostics we are modernizing the way infectious diseases are diagnosed and treated by developing a rapid diagnostic that sequences the genomes of pathogenic bacteria, and then uses machine learning methods to identify the cause of the clinical infection. We value intellectual curiosity and a strong work ethic.

Candidates will gain experience in a multidisciplinary and fast-paced start-up environment, and will have ample opportunities to acquire new skills, work closely with an accomplished team, and communicate results through patents, conference presentations, and peer-reviewed publications while working in a supportive and energetic environment.


  • Develop cloud-deployable machine learning and data analysis methods
  • Develop epidemiological tools for bacterial genome sequences
  • Develop pipelines to process large volumes of genomic data
  • Maintain organized, tested code and corresponding documentation
  • Present data within and outside of the company at meetings and symposia
  • Write, edit, and submit manuscripts/abstracts/grants detailing the results of the project
  • Work closely within the group and with outside collaborators
  • Maintain close communications with the team regarding progress


  • PhD with relevant experience in computational biology or bioinformatics
  • Fluency in Python, and Linux; familiarity with SQL and git
  • Familiarity with NGS data; familiarity with bioinformatics tools (alignment, variant calling, assembly, annotation); familiarity with ONT MinION data helpful but not necessary
  • TensorFlow, C, and GPU experience helpful but not necessary
  • Highly motivated and independent, with the ability to work in a dynamic team environment
  • Strong oral and written communications skills
  • Excellent organizational skills and attention to detail
  • Flexibility to occasionally work on weekends and evenings

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