Research Fellow in Optimization and Machine Learning of Flows in Complex Networks University of Melbourne, School of Mathematics and Statistics, Faculty of Science

RESEARCH FELLOW IN OPTIMIZATION & MACHINE LEARNING OF FLOWS IN COMPLEX NETWORKS


Job no: 0043594


Work type: Fixed Term


Location: Parkville


School of Mathematics and Statistics
Faculty of Science

 

Salary: $66,809 - $90,657 p.a. (Level A PhD entry level $84,458 p.a.) plus 9.5% superannuation

 

Two year Research Fellowship in Optimization and Machine Learning of Disrupted Flows in Complex Networks, aimed towards understanding, design and management of resilient networked systems. You will work with a multidisciplinary team working on challenges at the interface of research fields such as data analysis, computer science, operations research, and statistics.

 

Close date: 17 Sep 2017

 

Position Description and Selection Criteria

 

Download File 0043594.pdf

 

For information to assist you with compiling short statements to answer the selection criteria, please go to http://about.unimelb.edu.au/careers/search/info/selection-criteria

 

Advertised: 18 Jul 2017 12:00 AM AUS Eastern Standard Time
Applications close: 17 Sep 2017 11:55 PM AUS Eastern Standard Time


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