Job Description

TECHNICAL ASSOCIATE I, Sociotechnical Systems Research Center (SSRC), to join a team working at the intersection of single-cell measurement technology and gene therapy manufacturing within the Manalis Lab in the Department of Biological Engineering and in partnership with MIT’s Center for Biomedical Innovation.  The project explores the influence of biophysical states on cells’ capability to produce exosomes, a promising new class of therapeutics. Despite their potential to offer more effective treatments with reduced toxicity and immunogenicity, the development of exosome-based therapies faces considerable challenges, notably in manufacturing. The team aims to mitigate these challenges by leveraging a sophisticated microfluidic sensor platform combined with machine learning to analyze exosome-producing cells and elucidate the relationship between cell state and product quality.  Will perform routine data collection using advanced microfluidic sensor instrumentation to enhance understanding and ultimately aid in the commercial adoption of exosome therapeutic modalities.  Responsibilities include executing precise measurements using specialized in-house instrumentation to compile data on single-cell biophysical profiles; performing routine maintenance, including cleaning and calibrating instrumentation to ensure optimal performance; preparing samples for analysis using techniques like fluorescence labeling; and conducting basic cell culture tasks under stringent laboratory conditions.  

REQUIRED:  bachelor’s degree in biological, mechanical, or chemical engineering or a related field; two years’ lab experience; proficiency with standard wet-lab techniques, including pipetting and centrifugation; excellent troubleshooting and communication skills; meticulous attention to detail with sensitive measurements and delicate instrumentation; and ability to perform repetitive tasks, collaborate within a team, and commit to the timely delivery of research results.  PREFERRED:  experience with cell culture techniques, familiarity with flow cytometry, and proficiency with data analysis using MATLAB and/or Python.  Job #24018

5/9/24

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