Candidates are sought for the position of Postdoctoral Research Fellow in Adversarial Machine Learning, at the School of Computing and Information Systems, University of Melbourne, Australia. Applications close on 31 Jan 2018, with the position advertised at:
http://jobs.unimelb.edu.au/caw/en/job/892477/research-fellow-in-adversarial-machine-learning This project in "Adversarial Machine Learning for Cyber" aims to deliver new algorithmic and theoretical results on the robustness of machine learning systems in adversarial environments. We seek enthusiastic researchers with strong skills, including: machine learning algorithms (including reinforcement learning), nonlinear and convex optimisation, probability/statistical theory, programming. Experience with machine learning applied in computer security, game theory, robust statistics, or learning theory, a plus. The position offers a competitive salary of $87k AUD plus 9.5% superannuation (PhD entry level A6), and has duration 1 year with possibility of renewal. The School of Computing and Information Systems is an international research leader in computer science, information systems and software engineering. In this discipline, the School was ranked number 1 in Australia and 13th in the world in the 2016 QS World University Ranking exercise. The university is situated in the city of Melbourne, ranked by the Economist in 2017 as the world's most liveable city. The research group comprises Ben Rubinstein, Tansu Alpcan, Sarah Erfani, Chris Leckie at Melbourne - including pioneers in the field of adversarial machine learning with strong international collaborations - with project collaborators and sponsorship from Defence Science and Technology Group and CSIRO/Data61 (formerly NICTA). For queries please email the project lead CI, Ben Rubinstein at benjamin.rubinst...@unimelb.edu.au or visit http://bipr.net to learn more about the group. _______________________________________________ uai mailing list uai@ENGR.ORST.EDU https://secure.engr.oregonstate.edu/mailman/listinfo/uai
