Postdoctoral Position in Data-driven Graphical Models at ASU
Postdoctoral position at Arizona State University in using information sciences to model and learn graph-based representations of high-fidelity electric grid sychrophasor data in a data-driven fashion

Profs. Lalitha Sankar, Gautam Dasarathy, and Oliver Kosut at Arizona State University are looking for a postdoctoral fellow to work on developing graph-based models and representations for large spatio-temporal electric power grid synchrophasor datasets that can enable event and anomaly detection and identification.

The postdoc will be funded by an NSF HDR grant for an Institute for Data-Intensive Research in Science and Engineering (I-DIRSE) that researchers at ASU are leading. Eligible candidate should have a PhD in electrical engineering or computer science or mathematics/statistics. A strong background in information sciences (mathematics/statistics/probability/information theory/learning theory/statistical signal processing) is crucial.

Familiarity with or interest in learning electric power systems is desirable but not necessary.

Interested candidates should contact Prof. Lalitha Sankar with CV and publications at [email protected]