Connectionists: Open Post-doc Position in Active Efficient Coding (AEC)

[Jochen Triesch]

We have an opening for a post-doc position in my lab (http://fias.uni-frankfurt.de/de/neuro/triesch) at the Frankfurt Institute for Advanced Studies (FIAS) to explore the new area of active efficient coding (AEC), a recently formulated generalization of the efficient coding hypothesis to active perception.

The basic idea of AEC is that sensory systems learn to use their motor degrees of freedom to contribute to the efficient encoding of sensory signals. Along these lines, we have developed computational models for the self-calibration of active stereo and motion vision [1,2,3]. These models simultaneously learn a sensory representation with sparse coding approaches and controllers for their eye movements through reinforcement learning. Both learning components aim to maximize the overall coding efficiency of the system, which leads to fully self-calibrating sensory-motor loops for active stereo vision (dispartiy tuning and vergence control) and motion vision (motion tuning and pursuit movements). To the best of our knowledge, these models are the first to demonstrate how such self-calibration can emerge from a generic efficient coding objective. We have also validated the approach on robots such as the iCub (http://www.icub.org).

The work will be performed in a stimulating interdisciplinary environment with ample opportunities for collaboration with neuromorphic engineers, neuroscientists, roboticists, psychologists, and clinicians across the globe. A special emphasis will be on better understanding how and why such self-calibration can go awry in clinical conditions such as strabism and amblyopia.

We are seeking an outstanding and highly motivated post-doc for this project. Applicants should have obtained a PhD in Computational Neuroscience or a closely related field. The ideal candidate will have excellent programming skills (Matlab, Python, C/C++), very good analytic skills, and a broad knowledge of computational neuroscience, machine learning, computer vision, robotics, signal processing and statistics. Furthermore, specific expertise in visual neuroscience, sparse coding models, and reinforcement learning are requested. Experience with programming Graphics Processing Units (GPUs) is a plus. The position can be filled immediately, and lasts for 2 years. Extension to a third year is possible. The lab has an excellent track record of post-doctoral training with 6 out 11 post-docs having obtained professorships or other permanent academic posts directly after their time in the lab.

The Frankfurt Institute for Advanced Studies is a research institution dedicated to fundamental theoretical research in various areas of science. It is embedded into Frankfurt's recently established natural science research campus. Frankfurt itself is the hub of one of the most vibrant metropolitan areas in Europe. Apart from its strong economic and financial sides, it boasts a rich culture and arts community and repeatedly earns highest rankings in worldwide surveys of quality of living.

Applications should include a brief statement of research interests, CV and contact information for at least two references. Send applications to application at fias.uni-frankfurt.de. Review of applications will begin immediately. Interviews can be arranged at the upcoming Vision Science Society meeting in St. Pete Beach, Florida, USA, May 13-18 by emailing triesch at fias.uni-frankfurt.de.


[1] A Unified Model of the Joint Development of Disparity Selectivity and Vergence Control. Zhao Y, Rothkopf CA, Triesch J, Shi B. IEEE Int. Conf. on Development and Learning and Epigenetic Robotics (ICDL), 2012. (Paper of excellence award.)
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6400876

[2] Robust active binocular vision through intrinsically motivated learning
L. Lonini, S. Forestier, C. Teulière, Y. Zhao, B. Shi, J. Triesch, frontiers in Neurorobotics, 2013.
http://journal.frontiersin.org/article/10.3389/fnbot.2013.00020/full

[3] Self-calibrating smooth pursuit through active efficient coding
C. Teulière, S. Forestier, L. Lonini, C. Zhang, Y. Zhao, B. Shi, J. Triesch, Robotics and Autonomous Systems, 2014
http://www.sciencedirect.com/science/article/pii/S0921889014002486

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Prof. Dr. Jochen Triesch
Johanna Quandt Research Professor
Frankfurt Institute for Advanced Studies
http://fias.uni-frankfurt.de/~triesch/
Tel: +49 (0)69 798-47531
Fax: +49 (0)69 798-47611