Sr. Research Associate, High Throughput (HTP) Genome Engineering - Emeryville, CA | BioSpace
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Sr. Research Associate, High Throughput (HTP) Genome Engineering

Zymergen

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Location:
Emeryville, CA
Posted Date:
4/21/2017
Position Type:
Full time
Job Code:
Salary:
Required Education:
Bachelors Degree
Areas of Expertise Desired:
Associate, Chemical Engineering, Microbiology, Molecular Biology, Research, Senior Research Associate,

Job Description

Founded in 2013 and based in the San Francisco Bay Area, Zymergen is a technology company unlocking the power of biology. We deliver better economics for products made from biology that are used across industries, bring new products to market faster, and develop novel products. Our proprietary platform uses robots and machine learning to engineer microbes faster, more predictably, and to a level of performance previously unattainable. These microbes, and the products they produce, have broad applications across industries such as chemicals and materials, agriculture, and healthcare. For more information visit www.zymergen.com.

Zymergen is seeking a talented and experienced Sr. Research Associate to join our HTP Genome Engineering Optimization Group. The Sr. Research Associate will join a team responsible for improving and implementing the next generation of cloning and strain engineering technologies into our HTP Operations. The Associate will have an opportunity to work together with other scientists, automation and software engineers to deploy these new technologies, shape the HTP scientific environment, and establish best practices within a growing company.

Immediate responsibilities include:
•   Work with a team or lead the advancement of a high-throughput process from optimization and validation through to a successful Operations workflow.
•   Improve high-throughput techniques for the genetic engineering of various microbes, including those used for industrial production.
•   Optimize and implement molecular biology tools for an automated, high-throughput platform.
•   Work cross-functionally with automation and software engineers to efficiently release new processes and resolve problems.
•   Run process investigations and troubleshooting activities for high priority, time sensitive Operations.
•   Create, revise, and update standard operating procedures as needed
•   Provide Operations training and support of new workflows as needed

Requirements

We favor candidates who have shown independence in the lab and experience designing and executing their own experiments: MS with 6+ years working experience, or BS with 8+ years working experience or equivalent. Industrial experience is preferred. We are interested in candidates with technical training in molecular biology, microbiology, chemical or biochemical engineering, and related fields.

We prefer candidates with experience in some or all of the following areas:
•   Experience with microbial genome editing techniques of bacteria, yeast, or filamentous fungi. Those with experience optimizing techniques in a variety of organisms including atypical or industrial organisms will be given priority.
•   Experience with a variety of DNA assembly techniques (e.g. Gibson, SOE, yeast homologous recombination, Golden Gate, etc.)
•   Familiarity with applications of next-generation sequencing (NGS) for analyzing DNA and RNA samples.
•   Adept at utilizing automation (Agilent, Tecan, Beckman, and others) to assist with complicated or lengthy workflows.
•   Competence in using statistics, control charts, and the use of manufacturing practices such as Lean and 5S to develop efficient and effective lab processes preferred.
•   Familiarity with tools for DoE and the analysis of large datasets such as JMP or Spotfire, and the ability write scripts and perform data management functions in Python or SQL will be given priority.
•   Success in the technical transfer of materials and processes within an organization (e.g. with a high throughput screening or quality control team).
•   Experience mentoring and training others.
•   Experience working with LIMS databases.