Bioinformatics Software Engineer
Mountain View, CA /
Deepcell is an early-stage Stanford spin-off company that has developed a unique platform for use in research, diagnostic testing, and therapeutics. We combine microfluidics, imaging, deep learning, and genomics to identify, isolate and analyze live, single cells. Our technology addresses diverse applications in the life sciences.
Come join Deepcell and make a difference! We're a small team of passionate innovators in biomedical engineering, artificial intelligence, molecular biology, and genomics. Our technology has won multiple prestigious awards and is backed by top-tier venture capitalists in Silicon Valley.
Bioinformatics is an essential component of Deepcell’s technology. You will design, develop, test, deploy, maintain and improve robust computational workflows for the analysis and aggregation of genomic and transcriptomic datasets, integrating standard tools with proprietary algorithms. You will build tools that integrate the results of genomic analysis with Deepcell’s large and growing cell morphology database. You will support experimentalists in custom analyses of data from bioinformatics pipelines, and will work closely with engineering, software, biology, and data science teams on product development and external collaborations.
- 5+ years of industry experience building and deploying bioinformatics tools and workflows in a mature environment.
- MS with a focus in computational biology or related field, or equivalent industry experience
- Proficient in Python and strong data analysis skills
- Deep familiarity with the concepts, data types and standard tools in bioinformatics, genomics and NGS technology
- Well versed in software engineering best practices (version control, code review process, etc.)
- Passion for solving problems and for developing novel applications in biotechnology and medicine
- Effective communicator with biologists and engineers from different disciplines
- Expertise in statistical and machine learning methods
- Experience with workflow engines and workflow languages, especially those in use with Bioinformatics pipelines
- Experience with software development in a clinical/regulated environment.