Our efforts focus on quantitative imaging of cellular dynamics with the goal of improving measurement methods and reliability for the development, manufacturing and deployment of cell-based therapies. To carry this out, we are advancing the rate and volume with which image data can be acquired, processed, and analyzed. This work involves instrument development, computational methods for large biological image datasets, deep learning methods for dynamic analysis of living cells, massive integration of data and analysis, and AI validation. Computational work is performed in collaboration with the Software and Systems Division at NIST and https://www.nist.gov/itl/ssd/information-systems-group). In the Biosystems and Biomaterials Division we are particularly interested in collecting data from large numbers of single cells to characterize population phenotypes and understand their dynamics. We are examining how dynamic imaging of engineered fluorescent reporter cell lines enables the modeling of gene regulatory networks by statistical thermodynamics ( https://doi.org/10.1073/pnas.1207544109; https://doi.org/10.1371/journal.pone.0230076; https://doi.org/10.3390/e23010063; https://doi.org/10.1016/j.csbj.2020.09.025 ). We employ iPSCs and other cell types of interest to regenerative medicine and cellular engineering. Candidates should have experience in one or more of the following areas: live cell microscopy, systems biology, software engineering, AI computational methods, and theoretical modeling.
Interested parties please email Anne Plant.