LanzaTech’s unique multi-award winning technology captures and reuses waste carbon emissions as a resource for low carbon fuel and chemical production. This approach has no impact on land or the food value chain and enables sustainable economic growth for industry while promoting energy security. The company, named one of America’s most promising companies by Forbes Magazine in 2013, has received numerous sustainability awards including being listed on the Sustainia 100 in 2013 and the Global Clean Tech 100 for the past 3 years. LanzaTech currently holds the #2 position and the #4 position in Biofuel’s Digests’ Hot 50 rankings for bioenergy and Hot 30 rankings for renewable chemicals production. LanzaTech has developed commercial partnerships with global companies in the Petrochemical business, including oil majors Petronas and Indian Oil Corporation, steel industry giants Harsco and Siemens VAI, chemical companies including INVISTA, and global transportation companies including Virgin Atlantic. These partnerships cut across the full supply chain – from resources through to end users, positioning LanzaTech to become a global leader in low carbon commodity fuels and chemicals.
About The Role:
In this position you will perform comprehensive, high level, integrated analysis on pan omic data sets. Leveredging your analysis you will
- Suggest genome modifications and procedural improvements to perfect the performance of Lanzatech’s proprietary bacterial strains in production fermentation,
- Advance our systems level understanding the organism in order to accelerate and rationalize strain engineering,
- Enhance our existing, proprietary, highly predictive 3rd generation genome scale model
- Establish models of evolution occurring in fermenter populations, connect evolutionary events with underlying biology, and propose strategies to influence those evolutionary outcomes.
To achieve these goals, you will use and extend existing statistical and computational tools to integrate high volume omic data sets. You will work closely with scientists and engineers in the synthetic biology team, the strain development team and across the organization to address specific critical issues which they identify, and, you will reduce your findings to clear and informative visualizations and graphics and actively disseminate your results, conclusions and insights.
You are a team player who scrupulously documents your work. You are generous in shareing your knowledge with your team mates, and you expect to learn from them in return. You thrive in a agile goal oriented environment. Tou are cusdtomer oriented. You operate comfortably in Linux.
- Install, maintain and use bioinformatics software tools
- Integrate metabolomic, genomic, proteomic and transcriptomic data sets to solve deep biological problems
- Employ statistical computing to extract hypothesis and conclusions from these integrated data
- Contribute to ongoing re-annotation of bacterial genome and genome scale model refinement.
- Write scripts and utility programs in Perl, Python, or Bash.
- Provide bioinformatics support as requested by biologists in synthetic biology, strain development and other scientific group
- Design and implement data analysis pipelines
- Clearly document work and methods
- Communicate your findings, insights and conclusions to other scientific teams.
- Present summary of results to group in weekly meetings
Education & Experience:
- PhD in computational biology, quantitative biology, bioinformatics, computational genomics, computational systems biology or equivalent
- Significant exposure to prokaryotic biology with emphasis on metabolism, ideally to a gas fermenting acetogen
- Statistical computing in R in particular employing transcriptomics analysis packages, with documentation in jupyter notebooks
- Expert user of
- standard Bioinformatics tools such as MEME, BLAST, multiple sequence aligners, etc
- tools for handling and querying read alignments, such as samtools, bedtools etc
- tools for structure – sequence comparison such as Chimera or Phyre
- Expert NGS analyst including RNASeq
- Experience integrating metabolomics, genomic, proteomic and transcriptomic data sets to solve deep biological problems, especially in the context of metabolic pathways
- Accomplished utility programmer in Perl and/or Python
- Fluent in Linux ; working knowledge of windows
- Team player balanced with strong individual initiative
NICE TO HAVE
- Industry experience highly desirable
- Exposure to microbial fermentation highly desirable
- Experience in statistical learning highly desirable
- Experience in a high throughput environment highly desirable
- Front end development experience a plus
- Ruby/Rails and/or PHP development experience a plus
- Experience in building analysis pipelines
- Experience using / building Genome Scale Models
- Experience in synthetic biology
- Experience in Database Design, implementation and Administration in MySQL and PostgreSQL
- Unix system administration skills and experience
This position is open to candidates authorized to work in the United States on a full-time basis for any employer. LanzaTech is an Equal Employment Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.