Computational Biologist

Job ID:
Job date: 2018-06-18
End Date: 2018-08-17

Company : Ginkgo Bioworks 

Country : United States 

Role : Other 


[Click Here to Access the Original Job Post]

Job Description:
We are seeking a motivated Computational Biologist to join our growing team. Specifically, we are looking for individuals that are passionate about developing novel methods to ensure our engineered strains perform at peak capabilities.

As a member of the Computational Biology/Bioinformatics team, you will work closely with cross-disciplinary teams that include machine learning experts, software developers, and scientists to understand the analytical needs of our scientists working in our ground-breaking bio-manufacturing foundries. You will be able to use and further develop our repository of powerful and scalable analytical tools that can help derive unique insights from data produced by our scientists and from publicly available sources. Relevant data is derived from metabolic and evolutionary engineering, quantitative trait locus mapping, and metagenomics studies. It spans multiple host organisms and includes genomics, transcriptomics, proteomics and metabolomics, different data modalities (from phenotypes to metabolic models), and time scales (from single time points to continuous time series).

If you're interested in being a part of the next technological revolution, we want to hear from you!

Responsibilities:

  • Develop tools for comparative and phylogenetic analysis of genome and metagenome sequence data
  • Develop analysis framework for evolutionary engineering to improve strain performance
  • Implement sequence analysis tools for verification, analysis, and comparison of engineered strains
  • Develop tools for manipulation and analysis of NGS datasets
  • Integrate tools into Ginkgo's software infrastructure
  • Run existing analysis software and scripts as needed, while keeping excellent records
Requirements:
  • MS/PhD in life sciences, bioinformatics, computational biology, physical sciences, or equivalent experience
  • 4+ years of experience in computational biology and/or data analysis, including at least 2 years of hands-on work experience with real data (either in an academic or industry environment)
  • Loves to write elegant code (please provide a link to any publically available code when applying)
  • Experience with the data analysis stack of python (scipy, numpy, pandas, cobrapy) or R
  • Experience with manipulation and visualization of genome, metagenome and/or NGS datasets
  • Experience with NGS data from Illumina and MinIon sequencing machines, (de novo) genome and hybrid assembly, and genome annotation a plus
  • Ability to clearly communicate with multidisciplinary scientific staff in a collaborative and diverse environment


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Additional Info:
Our mission is to make biology easier to engineer. Ginkgo is constructing, editing, and redesigning the living world in order to answer the globe’s growing challenges in health, energy, food, materials, and more. Our bioengineers make use of an in-house automated foundry for designing and building new organisms. Today, our foundry is developing over 40 different organisms to make different products across multiple industries.

To learn more about Ginkgo, check out some recent press:

Ginkgo Bioworks secures $275 million in Series D, valuing the company at over $1 billion (TechCrunch)

Can This Company Convince You to Love GMOs? (The Atlantic)

Hundreds Of Millions Of Dollars Pour Into Hacking Microbes (Forbes)

We also feel it’s important to point out the obvious here – there’s a serious lack of diversity in our industry and it needs to change. Our goal is to help drive that change. We hope to continue to build a company whose culture promotes inclusion and embraces how rewarding it is to work with engineers from all walks of life. Making biology easier to engineer is a tough nut to crack – we can’t afford to leave any talent untapped.

It is the policy of Ginkgo Bioworks to provide equal employment opportunities to all employees and employment applicants.

[Click Here to Access the Original Job Post]