Are you interested in continual reinforcement learning (RL) in realistic environments where traditional RL (for board games etc) does not work well, where we need some sort of search for programs running on general purpose computers such as recurrent neural networks (RNNs), and where a good RL machine should learn to plan and reason in hierarchical and other abstract ways?

Join the Deep Learning team (since 1991) that won more competitions than any other. We are seeking PhD students and postdocs for Jürgen Schmidhuber's research group at the Swiss AI Lab IDSIA, for the RNNAIssance Project based on arXiv:1511.09249 on "learning to think." It is about general purpose artificial intelligence for agents living in partially observable environments, controlled by reinforcement learning RNNs, supported by unsupervised predictive RNN world models. Our first papers on such RL control systems based on two interacting RNNs date back to 1990 and 1991, but now, a quarter century later, finally we know how to do it right. (You will also collaborate with other lab members on other projects - we are one big family!)

Duration: initially for 2 years, with possibility of prolongation.

We are looking for outstanding candidates with experience / interest in topics such as deep learning neural networks, RNNs and Long Short-Term Memory (LSTM), evolutionary computation, RNN evolution, compressed network search, reinforcement learning & policy gradients for partially observable environments, unsupervised learning, curiosity-driven learning and the Formal Theory of Fun & Creativity, adaptive robotics, hierarchical reinforcement learning, general artificial intelligence, universal learning machines. The general goal is to advance the state of the art in machine learning and AI. Preferred start: As soon as possible.

INSTRUCTIONS: Submit your CV, a brief statement of why you'd like to work with us on such topics, and a list of 3 references and their email addresses to rnnai2016@idsia.ch. In the subject header, mention your full name followed by the keyword rnnai2016. (Add "PhD" in case of PhD students. For example, if your name is Jo Mo, and you are applying as a PhD student, use subject: Jo Mo rnnai2016 PhD)

As a PhD student, you must also submit your material to SUPSI through THIS ONLINE FORM (now closed). As a postdoc, you must also submit your material to SUPSI through THIS ONLINE FORM (open again until Oct 31).

PhD student salary: Initially CHF 46'000 per year (>US$ 46k as of 21 Oct 2016). Standard postdoc salary: CHF 80'000 per year (>US$ 80k as of 21 Oct). Low Swiss taxes. There is travel funding in case of papers accepted at important conferences. There are also exciting connections to the world of AI startups.

There is an opportunity to participate in teaching courses (in English) on machine learning, e.g., in the master's program at the University of Lugano.

Requirements are also published within the "Direttive interne SUPSI" (direttiva 7A, Art. 2) and within "Regolamento del personale SUPSI" on the website www.supsi.ch (follow SUPSI, Documenti ufficiali). Official language at IDSIA is English.

(Filled: one additional 4-month PhD student position in the Prototouch project with this online form.)