Creating, screening, and modelling multiplexed reporters of cell state

Theme: World-Class Underpinning Bioscience

The PhD project aims to create tools and methods for measuring several cell state features at once. The first goal is to make use of recently developed modular cloning techniques to introduce multiple transcriptional response based reporter elements into the human genome. In parallel, image analysis methods based on deep convolutional neural networks will be developed to accurately infer the reporter activity from high throughput microscopy images. After validating faithfulness of the reporter and the quality of analytical methods, cell state will be monitored in various conditions and knock-out backgrounds to identify its modulators.

The project involves ENWW in both experimental and computational aspects. Experimentally, the goal is to measure more features of living cells than has been possible before with cutting edge mammalian synthetic biology techniques. Computationally, novel methods based on deep neural networks will be implemented to analyse the produced data.