New measurement methods and tools are required for biology to emerge fully as an enabling, practical platform for engineering. The Cellular Engineering Group works to provide a foundation of measurement assurance to support the control and rational design of biological function. Through state of the art synthetic biology, automation, and machine learning, the Group creates living measurement systems, such as cells, engineered to sense and respond in programmed ways. Importantly, building these systems both requires and advances meaningful quantitation of the effects of environmental context and evolution. The Group aims to advance fundamental understanding, improve predictability for design, ensure reproducibility and comparability, and facilitate scalability for real-world applications of engineered biological systems.
We are seeking applicants interested in the following and related technical areas:
· Experimental and theoretical research to advance rational design for engineering biology. Of particular interest is the development of new approaches to measure, understand, predict, and control information, learning, function, and evolution across the spatial and temporal scales of biological organization, although related ideas in other topics are welcome.
· Absolute quantitation for engineering biology, in which mechanistic studies of gene expression are applied towards enabling more predictive engineering of living organisms. We welcome applicants with previous experience applying single-molecule techniques to understand energetics, thermodynamics, kinetics of protein-DNA interactions, and related phenomena, and connecting these measurements to organism fitness.
· Cell-free systems for engineering biology, in which cell-free systems, engineering subcellular confinement, minimal life, synthetic cells, and related topics are investigated towards control and rational design of biological function.
· Automation for engineering biology, in which methods are developed to create a measurement infrastructure for engineering biology. Collaborating with a multidisciplinary team, automation methods will be demonstrated to facilitate rapid and flexible adoption of automation systems for a variety of biological measurements.
We are seeking independent, articulate, and motivated individuals with backgrounds across the physical, engineering, chemical, and biological disciplines to contribute to our collaborative, interdisciplinary Team. Facilities include state of the art systems for automated microbial engineering, culture, and measurement, single-molecule fluorescence microscopy, and cleanroom fabrication and characterization.
Synthetic biology; Genetic circuit; Evolution; Biophysics; Fluorescence microscopy; Flow cytometry; Microfluidics; Fitness landscape; Bacteria; yeast;
FISH; HCR; single molecule; engineering biology; transcription; microscopy; information theory; systems biology;
cell-free system; control engineering; genetic circuit; genetic sensor; minimal cell; synthetic cell; TX-TL; in vitro expression system;
automation; evolution; flexible automation; machine learning; artificial intelligence; active learning