We have a 4 year Lecturer Position available at QUT to work closely with my research group at the boundary between robotics, neuroscience and computer vision, developing Frankenstein models of visual and spatial intelligence that combine the best performing and best understood parts of human, animal and insect brains.

Here’s the ad: http://tinyurl.com/nzdujv3

Some of the highlights:

· You’ll get to push the boundaries of our understanding of the brain and how we can model it to create new technologies and capabilities for robotics and AI

· Minimize that start-up lag: you’ll land in the middle of a large research group and have the opportunity to immediately get involved in the supervision of several PhD students working in the area – in fact, your ability to effectively lead and supervise PhD students is critical to this role

· Tap into collaborations with some of the world’s top roboticists, neuroscientists and computer vision researchers at leading international institutions including David Cox at Harvard University, Michael Hasselmo at Boston University, Andrew Davison at Imperial College London, Barbara Webb at Edinburgh University and many more.

· Get access to top local researchers and major projects including the $19,000,000 Australian Centre for Robotic Vision, the $676,000 project this position is associated with, as well as multiple other projects including a $3,000,000 Strategic Investment in Farm Robotics.

· You’ll have the opportunity to teach into some of the most fun, engaging and fulfilling robotics-related units at our university. Videos of some of the units we teach can be found at https://youtu.be/FBEINbpovBE and https://youtu.be/_2mp98Sk6fQ.

· Work in the heart of Brisbane, a modern bustling city of 2 million people, located near to amazing beaches and vast swathes of untouched wilderness. If you love hiking / running / cycling / swimming / surfing / parasailing, you can find it here. Catch a short flight and you’re on the Great Barrier Reef or in the Barossa Valley.

· Be immersed in a large, very successful and sociable robotics group of more than a hundred academics, postdocs and students, in a brand new building space.

Here’s the ad again: http://tinyurl.com/nzdujv3

Best regards,

Michael

Michael Milford Associate Professor | ARC Future Fellow | Microsoft Faculty Fellow | Chief Investigator, Australian Centre for Robotic Vision
Australian Centre for Robotic Vision | Electrical Engineering and Computer Science School
Science and Engineering Faculty | Queensland University of Technology

S Block, Room S1110, Gardens Point Campus

ph 3138 9969 | email michael.milford@qut.edu.au
CRICOS No 00213J

More information available at: https://wiki.qut.edu.au/display/cyphy/Michael+Milford

Google Scholar Profile: http://scholar.google.com/citations?user=TDSmCKgAAAAJ&hl=en

MilfordRobotics Youtube Channel: https://www.youtube.com/user/milfordrobotics

* Highlighted Publications *

* Review of Robotics and Biological Navigation Principles- "Principles of goal-directed spatial robot navigation in biomimetic models", Philosophical Transactions of the Royal Society B, link http://rstb.royalsocietypublishing.org/content/369/1655/20130484

* Visual Place Recognition Under Extreme Perceptual Change - "SeqSLAM: Visual route-based navigation for sunny summer days and stormy winter nights", International Conference on Robotics and Automation, link http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6224623

* Navigating without GPS, using only a web camera - "Mapping a Suburb with a Single Camera using a Biologically Inspired SLAM System", IEEE Transactions on Robotics, link http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4627450

* Continual mapping and navigation over a 2 week office delivery robot experiment - “Persistent Navigation and Mapping using a Biologically Inspired SLAM System", International Journal of Robotics Research, http://ijr.sagepub.com/content/29/9/1131.abstract

* Combining robotics, neuroscience and animal navigation to manage uncertainty when navigating - “Solving Navigational Uncertainty Using Grid Cells on Robots”, PLoS Computational Biology, http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000995