Available Positions

Postdoctoral Research Associate Positions

We are hiring continuously.  Postdoctoral positions are available for dynamically changing large-scale network modeling project at the University of Wisconsin-Madison. The candidates will work with professor Moo K. Chung on developing new innovative computational, statistical and machine learning methods for large-scale brain networks obtained from fMRI and DTI scanners that are dynamically changing over time. 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 neuroimaging research experience is a plus but not necessary. The candidates are expected to have emerging tract records of publishing in journals and conferences, strong analytic and writing skills and capable of working within a collaborative environment. Expertise in the following areas would be useful but not critical: large-scale computation (matrices), dynamic models (time series), topological data analysis, deep learning (Boltzmann machine),  computer vision (geometry & shapes).

Interested candidates should email CV (with the name of references) and representative papers to Moo K. Chung (mkchung@wisc.edu).

We are also looking for capable graduate students

Representative papers written by graduate students and postdocs as the first authors:

Huang, S.-G., Lyu, I., Qiu, A., Chung, M.K. 2020. Fast polynomial approximation of heat kernel convolution on manifolds and its application to brain sulcal and gyral graph pattern analysis, IEEE Transactions on Medical Imaging 39:2201-2212

Wang, Y., Ombao, H., Chung, M.K. 2018 Topological data analysis of single-trial electroencephalographic signals. Annals of Applied Statistics, 12:1506-1534 (
received ENAR paper award)

Lee, M.-H., Kim, D.-Y., Chung, M.K., Alexander, A.L., Davidson, R.J. 2018 Topological properties of the brain network constructed using the epsilon-neighbor method in patients with autism, IEEE Transactions on Biomedical Engineering, 65:2323-2333 (selected for cover art)

  1. Hosseinbor, A.P., Chung, M.K.,  Schaefer, S.M., van Reekum, Perchke-Schmitz L., Sutter, M., Alexander, A.L., Davidson, R.J. 2015 4D hyperspherical harmonic (HyperSPHARM) representation of surface anatomy: a holistic treatment of multiple disconnected anatomical structures, Medical Image Analysis 22:89-101

  1. Kim, W.H., Pachauri, D., Hatt, C., Chung, M.K., Johnson, S.C., Singh, V. 2012. Wavelet based multi-scale shape features on arbitrary surfaces for cortical thickness discrimination, Advances in Neural Information Processing Systems (NIPS) (acceptance 25.2%)

Lee, H., Chung, M.K., Kang, H., Kim, B.-N., Lee, D.S. 2011. Computing the shape of brain network using graph filtration and Gromov-Haudorff metric. 14th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI). Lecture Notes in Computer Science (LNCS). 6892:302-309.  (selected for oral, oral acceptance 4.15%)

  1. Seo, S., Chung, M.K., Voperian, H.K. 2010. Heat kernel smoothing using Laplace-Beltrami eigenfunctions. 13th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI). Lecture Notes in Computer Science (LNCS). 6363:505-512. (acceptance rate < 32%).

  2. Lee, J.E., Chung, M.K., Lazar, M., DuBray, M.B., Kim, J., Bigler, E.D., Lainhart, J.E., Alexander, A.L. 2008. A study of diffusion tensor imaging by tissue-specific, smoothing compensated voxel-based analysis.NeuroImage 44:870-883.