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Computational Biologist, Single Cell Technology Dev

Employer
Mission Bio
Location
South San Francisco, California, US
Salary
Competitive
Closing date
Sep 9, 2021

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Sector
Academic / Research
Field
Informatics / GIS
Discipline
Statistics
Salary Type
Salary
Employment Type
Fellowship
Are you curious, driven, and collaborative? Do you want to work at one of the most innovative and impactful biotech companies in the Bay Area? Mission Bio's Tapestri Precision Genomics Platform was #2 on the TheScientist's 2018 Top 10 Innovations list. And single-cell sequencing, which we focus on, was voted Nature Methods Method of the Year 2019. Our mission is to enable our customers to eliminate cancer.

Mission Bio is a start-up providing the best-in-class solution for single-cell genomics, ranging from research to translational/clinical medicine. We are a small team that is growing rapidly, so this is an opportunity for a talented, driven individual to significantly impact the direction and success of an exciting young company. We are committed to diversity. If you are a collaborative, curious, hardworking professional who thrives in a fast-paced, dynamic, supportive environment, we would love to meet you.

ESSENTIAL DUTIES AND RESPONSIBILITIES (Other duties may be assigned)

We are looking for a highly motivated and experienced Computational Biologist to join a growing team of bioinformaticians and assay development scientists dedicated to improving and expanding Mission Bio's single cell genomic and multi-omic assays. The successful candidate will be responsible for working closely with molecular biologists and microfluidics engineers in order to add to and expand the multi-omics capabilities of our Tapestri platform. The candidate will apply cutting edge data analysis techniques in order to interpret the results of experiments designed to improve our commercial products as well as guide future experimental design. In addition to fellow scientists, you will also work cross-functionally with our product and commercial teams as well as customers to translate findings into exciting multi-omics products.
  • Develop and apply data analysis methods to next-generation sequencing datasets in order to guide development of a variety of single cell applications as well as identify new product opportunities.
  • Analyze both internally generated as well as public datasets to extract biological insight and generate testable hypotheses.
  • Work with assay development scientists to design experiments expanding the capabilities of Mission Bio's single-cell Tapestri instrument.
  • Build analysis tools and performance metrics that will allow continual monitoring of assay performance.
  • Communicate analysis results to internal and external stakeholders via presentations and written documentation.
  • Collaborate with scientists, marketing, and customers to support project planning and commercial launch

QUALIFICATIONS, EDUCATION AND EXPERIENCE

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. The candidate should have:
  • PhD (or M.Sc. with 3+ years of industry experience) in computational biology, bioinformatics, statistics, or related quantitative fields (industry experience preferred).
  • Strong background in analysis of large, multi-sample NGS datasets (single-cell preferred) - from raw reads to processed data. Knowledge of functionality and use of key bioinformatics tools and packages. Firm understanding of statistical modeling methods and machine-learning applications.
  • Experience working with single cell data and/or good understanding of the signal/noise relationships in single cell or similar datasets. Experience with multi-omics product development a strong plus.
  • Expertise in at least one common programming language applied to data analysis (Python preferred, working knowledge of R a plus).
  • Excellent communication and teamwork skills to work with both experimental and computational scientists in a collaborative environment.


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