We are seeking a Postdoctoral Research Fellow for a (up-to) 3-year position to work on an exciting project funded by the Medical Research Council and led by Dr Bingxin Lu (https://icelu.github.io/) at the University of Surrey.
The application deadline is 30 Apr 2025. Please see http://jobs.surrey.ac.uk/017125 for more details.
This project aims to reconstruct the evolutionary dynamics of chromosomal instability in cancer genomes. Understanding how chromosomal instability evolves during the progression from precancerous lesions to malignancy, metastasis, and treatment resistance is important for cancer detection and treatment. Building upon our previously published method, CNETML (https://doi.org/10.1186/s13059-023-02983-0), this project will develop more realistic evolutionary models of copy number alterations and better phylogenetic inference methods with wider applicability. The developed methods will then be applied to extensive publicly available datasets to investigate the dynamics of chromosomal instability. Our new methods will enhance the toolkit for cancer researchers and drive broader applications of cancer phylogenetic inference. The insights gained from the inferences will also support personalized therapy and advance public health efforts.
The application deadline is 30 Apr 2025. Please see http://jobs.surrey.ac.uk/017125 for more details.
This project aims to reconstruct the evolutionary dynamics of chromosomal instability in cancer genomes. Understanding how chromosomal instability evolves during the progression from precancerous lesions to malignancy, metastasis, and treatment resistance is important for cancer detection and treatment. Building upon our previously published method, CNETML (https://doi.org/10.1186/s13059-023-02983-0), this project will develop more realistic evolutionary models of copy number alterations and better phylogenetic inference methods with wider applicability. The developed methods will then be applied to extensive publicly available datasets to investigate the dynamics of chromosomal instability. Our new methods will enhance the toolkit for cancer researchers and drive broader applications of cancer phylogenetic inference. The insights gained from the inferences will also support personalized therapy and advance public health efforts.