Physics-Based Machine Learning for Subcellular Segmentation in Living Cells

Physics-based machine learning for subcellular segmentation in living cells

Segmenting subcellular structures in living cells from fluorescence microscope images is a ground truth (GT)-deficient problem. The microscopes’ three-dimensional blurring function, finite optical resolution due to light diffraction, finite pixel resolution and the complex morphological manifestations of the structures all contribute to GT-hardness. Unsupervised segmentation approaches are quite inaccurate. Therefore, manual segmentation relying…

Research Associates in Physics-inspired/physics-based computing

We invite applications for up to two postdoctoral Research associates in physics-inspired/physics-based computing at the Department of Applied Mathematics and Theoretical Physics. The successful appointees would be expected to start any time before October 2025 for two years. One position will be funded by the UK multidisciplinary centre for neuromorphic computing. Candidates should be qualified to undertake research topics on quantum to classic…