MOO CHUNG
Postdoctoral positions are available at the University of Wisconsin-Madison. The candidates will work with professor Moo K. Chung (www.stat.wisc.edu/~mchung) on developing new innovative computational methods in modeling large-scale dynamically changing graph and simplical complex data structures. Candidates should be familiar with one of areas: dynamical systems including time series, statistical physics (particularly Ising model), signal and image analysis, network science, graph theory, algebraic topology, topological data analysis, partial differential equations (computational), artificial neural networks (ANN). Candidates should have received or expected to receive PhD degree or equivalent in mathematics, physics, CS, EE, statistics, biomedical engineering, psychology, neuroscience or related areas. Previous imaging research experience is a plus but not necessary but programming skill is a must. Interested candidates should email CV (with the name of references) and representative papers to mkc...@wisc.edu. There is no deadline for the positions and we are hiring year round.
The following are two recent publications from our group: Topological learning on networks (Annals of Applied Statistics: arXiv: 2012.00675), Hodge Laplacian for higher order network connectivity (IEEE Transactions on Medical Imaging: arXiv:2110.14599).