Computational Engineer - LIMS

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The successful candidate will work closely with scientists, computational biologists and other computational engineers to facilitate movement of information in and out of our LIMS/ELN, build, optimize and maintain pipelines to automate lab processes and analyze lab data, and build infrastructure that is robust across time and teammates.  This person will have strong written and verbal communication skills paired with an ability to get things done quickly without amassing hidden technical debt.  They will be able to work with scientists, automation engineers, and computational biologists to understand their requirements, negotiate solutions that satisfy those requirements, and implement them in a timely fashion.

The ideal candidate will be excited about increasing the accuracy and efficiency of our lab activities by automating repetitive or error-prone tasks and bioinformatics analyses, allowing us to increase breadth and depth of our work.  They will believe in the importance of building systems that are approachable and maintainable by using standard tooling and techniques; implementing test cases; using version control and continuous integration systems; and writing documentation for end-users and other developers. The ability to be flexible, and to work in a highly collaborative environment and an agile team first mind-set will be critical to success.

  • Develop tools and pipelines to integrate with laboratory equipment, LIMS and ELN in an automated, robust and reproducible fashion within the Sana informatics infrastructure.
  • Build, deploy, and maintain analysis pipelines that are efficient, robust, and leverage multicore compute resources while following best practices in software engineering (e.g. version control, code review, tests, documentation, CI/CD).
  • Write software to drive robotic liquid handlers and similar devices.
  • Design and run computational tests to validate results and assess performance of pipelines.
  • Collaborate with the Computational Biology group to help build core informatics infrastructure, tooling, and software development processes.
  • Work with teammates to produce production-ready implementations of analyses developed in Computational Biology.
  • Design and run computational tests to validate results and assess performance of pipelines
  • Build Shiny apps with user friendly interfaces and/or Spotfire dashboards that deliver results and reports to end users.
  • Mentor computational biologists to review and test code; refactor prototype workflows into automated pipelines as necessary.
  • Communicate to a broad audience with a range of technical, analytical, and biological expertise and present results on a regular basis at various group meetings.


Required Qualifications
  • PhD in scientific/technical discipline and up to 2+ yrs academia or industry experience. BA and/or MS plus 7+ yrs or equivalent combination of education and work experience.
  • 3+ years of hands-on experience with automating laboratory systems.
  • Demonstrated proficiency in Python required, with experience in Python documentation tools and software best practices.
  • Demonstrated proficiency writing software that interacts with HTTP APIs.
  • Routine use of version control (e.g. git) to manage and organize the evolution of software projects.
  • Demonstrated strong problem-solving abilities and organizational skills.
  • Must be detail oriented, self-motivated, independent, flexible, and able to prioritize and manage several fast-paced projects concurrently.
  • Strong verbal and written communication skills for technical and non-technical audiences.
  • Experience with high performance computing (local or cloud) and proficiency in *ix.
  • Minimum of 4 years hands-on experience with software development cycle (e.g. git, code review, testing, documentation).
  • Good knowledge of informatics, IT infrastructure for Bioinformatics, data storage and management of large data.
  • Demonstrated ability to work in cross-functional teams as a strong team player as well as independently.

Preferred Qualifications
  • Experience with the Benchling ELN/LIMS system.
  • Experience with C#, C, C++, and/or other compiled languages.
  • Experience managing computations and data in hybrid cloud/on-premises computing environments.