Post-MS
Supports the Cellular Engineering Group and NIST Engineering Biology Program by advancing measurement assurance for cell-free systems from diverse samples, including reconstituted and microbial samples. Assist in advancing metabolic engineering and scale-up for cell-free systems. Assists in the automation of reagent preparation, cell-free reaction assembly, and, for using NIST Living Measurement Systems Foundry (LMSF) or other laboratory automation. Analyzes experimental and simulation data, including uncertainty and other statistical analyses. Documents and manages manual and automated laboratory protocols, data, and analyses. Regularly presents and discusses progress with the larger organization.
Plans and carries out difficult and complex assignments in a scientific, engineering, mathematics, or information technology discipline with limited supervision. Develops new methods, approaches, and procedures usually in cooperation with coworkers or advisors. Works with peers and others to develop resolutions to complex or challenging issues and provide recommendations for improvements to meet program objectives. Completed work is expected to have a sound overall approach and effectively meet stated requirements. Work impacts the technical planning, completion, and direction of major scientific, mathematical, engineering, or information technology projects.
Metabolic engineering for cell-free expression
- A Master’s degree in chemical engineering, bioengineering, cell biology, chemistry, physics, synthetic biology, or a related field.
- 3 years of relevant experience.
- Strong oral and written communication skills.
Key responsibilities will include but are not limited to:
- Developing assays to characterize the metabolism and scale-up of cell-free reactions.
- Investigating experimental and analytical means to support measurement assurance for cell-free systems.
- Assisting with the automation of methods for preparation of cell-free lysates, cell-free reagents, cell-free reaction assembly, and assaying cell-free systems and their performance.
- Analyzing heterogeneous data sources, including uncertainty and other statistical analyses.
- Presenting results at internal meetings, and occasional meetings with external stakeholders.
- Ensuring that results, protocols, software, and documentation have been archived or otherwise transmitted to the larger organization.