PhD Position on Dynamical Models Learning for 3D Cell Imaging Data
Live-cell 3D microscopy is revealing biology at a breathtaking spatio-temporal scale, but today’s object trackers still struggle with dense scenes, extreme shape changes and hour-long recordings. Our new project brings together cutting-edge imaging at the Princess Máxima Imaging Center with state-of-the-art visual-tracking research in the Video & Image Sense Lab to solve this bottleneck.
We will develop an unsupervised or semi-supervised, end-to-end cell tracker that links every pixel belonging to the same cell across space and time, automatically adapts to complex deformations and recognises functional patterns such as T-cell serial killing in solid-tumour organoids. By delivering accurate, long-term trajectories we open the door to quantitative “cell-centric representations” that can drive both fundamental discovery and next-generation immunotherapies.
