Arc Institute-posted about 16 hours ago
$122,500 - $152,500/Yr
Full-time • Mid Level
Palo Alto, CA
101-250 employees

The Arc Institute is seeking a Bioinformatics Engineer to join the Bioinformatics team within the Computational Technology Center. The successful candidate will play a crucial role in advancing the Arc’s Virtual Cell Initiative, which aims to create the machine learning models that make accurate predictions of cellular states and their responses to perturbations, and ultimately to help identify rational therapeutic targets for complex human diseases.

  • Implement, test, and maintain state-of-the-art analysis pipelines for various high-throughput projects using best software engineering practices.
  • Run the production pipeline for large-scale production datasets and provide quality assurance to experimentalists and technologists.
  • Process sequencing data as they come off instruments, monitoring runs, producing actionable results and troubleshooting issues to ensure timely delivery of results.
  • Support multiple concurrent projects across different Technology Centers, requiring effective context-switching between different experimental approaches.
  • Partner with experimentalists to troubleshoot analyses and help interpret pipeline outputs.
  • Manage code repositories on GitHub, document workflows, and maintain computational environments to ensure pipeline reliability.
  • Rapidly learn novel wet-lab technologies, benchmark and master emerging computational methodologies.
  • Assist others in utilizing software packages and pipelines.
  • Bachelor or Master degree in Bioinformatics, Computational Biology, Computer Science, or related quantitative fields.
  • 2-5 years of experience analyzing high-throughput sequencing datasets, especially single-cell omics data.
  • Strong software engineering skills, including testing, documentation, and version control.
  • High competency with Python, git/GitHub, and Linux.
  • Excellent communication skills and ability to effectively collaborate with wet-lab scientists.
  • Strong statistical, mathematical, analytical, and data science skills.
  • Familiarity with cloud computing.
  • Familiarity with CRISPR screens technology and analyses.
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