Research Associate Flow-Cytometry
il y a 4 semaines
Job description
The “LESAFFRE Biofoundry” (LESAFFRE Bioengineering team) – Lille Metropole conjunction to a second Gene Editing Synthetic Biology hub in the USA and deliver to the Lesaffre’s Mission of “Working together to better nourish and protect the planet.”
Our Approach: We build an international team of motivated, risk-taking scientists and engineers to merge biology, engineering, automation, informatics to improve organism engineering, screening and selection for a wide portfolio of fermentation applications.
Our Scope: We engineer, screen, select yeast and bacteria for industrial biotechnology applications including baking, brewing, bioethanol, flavors and fragrances, food and feed, nutraceuticals, pharmaceuticals.
As our Research Associate focus on Flow-Cytometry / Microfluidic, your main responsibilities will be :
Developing and operating automated Flow cytometry assays for selection of Yeasts and other microorganisms. Developing and operating automated advanced droplet microfluidics assays for selection of Yeasts and other microorganisms. Organizing and supporting the validation and QC’ing of automated biological screening protocols . Training of team members to protocols, workflows, and best practices. Working with automation engineers, assay development scientists, metabolic engineering scientists and data scientists to ensure the technical quality. Identifying and leading improvements in group practices and protocols.Qualifications
Mandatory:
Engineer or MSc in biology, cell biology, biochemistry, bioengineering, chemistry, chemical engineering or equivalent. Demonstrated ability to work on single cell characterization/analysis such as, flow cytometry, FACS sorting, droplet microfluidic. Strong organizational skills.Prefered:
Demonstrated ability to develop novel cell-based screening assays is a plus. Expertise in current technology and applications in microfluidics is desirable; hands on experience, development and micro-fabrication of microfluidic devices is a plus. Data and statistics background; ability to script simple data analysis in one the following, Matlab/Octave, Python or R is a plus. PhD or 2-year industry research experience in biotechnology, assay development, or high/ultra-high throughput screening is a plus. Familiar with diverse micro-organisms is a plus. Knowledge of LIMS environments (e.g. Benchling) as well as statistical software packages (MiniTab, SPSS, etc.) is a plus. Automation of data analysis of FACS and/or cytometry is a plus.-
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