Postdoc Pönisch Lab
Pubblicato il 10-09-2026 - Altro in Milano
Build the science that shapes the future of human health.
Application closing date: 06.09.2026
Join a place where ambitious science thrives
Human Technopole (Milan) is a rapidly expanding life science institute where international researchers and cutting-edge technologies converge to accelerate biomedical discovery. Our mission is to transform bold scientific ideas into advances that improve human health.
Within this mission, the newly established Pönisch Group studies how biological matter changes shape during development and disease. We combine quantitative image analysis, morphometrics, and theoretical modelling to uncover the principles underlying stochastic shape dynamics in biological systems. We study these questions across scales, from the shape dynamics of single cells to dynamic behaviours in cell collectives and tissues. We are a theory lab, working at the interface of physics, data science, and biology and in close collaboration with experimental partners.
We seek an ambitious postdoc to study how individual cell morphodynamics is coupled to cell topology and cellular state in cell collectives.
The successful candidate will analyse large imaging datasets of in vitro cell aggregates and biological tissues and develop a multimodal analysis framework to represent collective cell dynamics as a low-dimensional stochastic dynamical system.
The aim of this project is to distinguish intrinsic from extrinsic contributions to the stochastic morphodynamics of cells and to develop a holistic understanding of the collective behaviour of biological matter.
Working closely with experimental collaborators, the new lab member will integrate data analysis and theoretical physics to identify general principles driving collective cell dynamics.
Grow Your Skills
You will enhance your scientific and professional skills by working with:
Imaging datasets of cell collectives generated in collaboration with experimental partners.
Advanced bioimage analysis, including image segmen