Two Postdoctoral research fellow positions at the University of Melbourne's Department of Computing & Information Systems

Join a world-class research group in one of two open postdoctoral research fellow positions at the University of Melbourne's Department of Computing & Information Systems, situated in one of the world's most liveable cities. Applications close end of February.

The first position is in adversarial machine learning. Little is known about how well state-of-the-art inference techniques fare when data is manipulated by a malicious adversary; this project aims to evaluate the robustness of broad classes of learners using tools from optimisation, and to explore consequences of robustness to computer security. This position is funded by an Elon Musk-backed grant from FLI. Further details:

http://jobs.unimelb.edu.au/caw/en/job/887407/research-fellow-in-adversarial-machine-learning

The second position is to research machine learning and systems. Topics span probabilistic databases, adaptive importance sampling, crowd sourcing, data integration, machine learning workflows. This position is funded by an Australian Research Council grant "Democratising Big Machine Learning". Further details:

http://jobs.unimelb.edu.au/caw/en/job/887416/research-fellow-in-machine-learning-systems

Both positions offer a competitive salary of $82k AUD plus 9.5% superannuation (PhD entry level A6). Applications close at the end of February via the links above.

For queries please email the project CI, Ben Rubinstein at benjamin.rubinstein@unimelb.edu.au Or visit http://bipr.net to learn more about the research group which has strong international collaborations and connections to industry. The CI will be at AAAI'16 this month.

Close date: 1 Mar 2016

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