A Postdoctoral Fellowship is available immediately in the Peccoud Lab to support a research project aiming at using methods from synthetic biology to generate big datasets suitable to support the development of large-scale models of regulatory networks in yeast. We are seeking an exceptional and innovative individual with a degree in molecular biology, biochemistry, bioengineering, chemical engineering or a related field to join a multidisciplinary team composed of synthetic biologists, computational biologists, and computer scientists. This person will be responsible for developing and managing a high-throughput pipeline to generate and characterize libraries of complex yeast mutants. Prior experience in yeast genetics and/or editing of microbial genomes is required. This position requires the ability to work in a highly collaborative environment with team members having a broad range of scientific backgrounds and levels of experience. In addition, this position will be involved in the training and management of undergraduate or graduate students, development of new proposals, and day-to-day management of scientific collaborations.

 

Required Qualifications

  • Doctoral degree in molecular biology, biochemistry, bioengineering, chemical engineering, or a related field
  • Experience with genome editing technologies, strain engineering, or high throughput genetic screens in yeast or other microorganisms.
  • Track record of peer-reviewed publications.
  • Effective oral and written communication skills.

 
Preferred Qualifications

    • Familiarity with synthetic biology workflows
    • Experience with high-throughput projects
    • Ability to manipulate and analyze data in Matlab, Python, R, or other languages.
    • Experience with standard bioinformatics tools and resources
    • Experience developing or using quantitative models of regulatory networks.

 

Additional information and application instructions available at   https://jobs.sciencecareers.org/job/503158/postdoctoral-fellow-yeast-synthetic-biology/?TrackID=148656

2019-08-26T15:53:00+00:00