Postdoc position developing Bayesian-TDA

Jan 4, 2021

Multiple postdoctoral positions are available for a dynamic network modeling project at the University of Wisconsin-Madison. The candidates will work with Professor Moo K. Chung ((Use the "Apply for this Job" box below)./~mchung) on developing innovative computational, statistical, and machine learning methods for large-scale brain networks obtained from fMRI and DTI scanners that change over time. Candidates should have received or expect to receive a PhD degree or equivalent in mathematics, physics, computer science, electrical engineering, statistics, biomedical engineering, psychology, neuroscience, or related fields.

Previous neuroimaging research experience is a plus but not required. Candidates should have a track record of publications in journals and conferences, strong analytical and writing skills, and the ability to work collaboratively. Relevant expertise includes, but is not limited to: large-scale computation (matrices), dynamic models (time series), topological data analysis (graph theory, combinatorial optimization), deep learning (Boltzmann machines), and functional data analysis (functional PCA).

Interested candidates should email their CV (including references) and representative publications to Moo K. Chung  position will be advertised until filled.