Schickard Leibniz Gauss Kurt Goedel Ray Solomonoff at IDSIA Konrad Zuse Turing Archimedes, greatest scientist ever?
Very Deep Learning since 1991
Our impact on the world's most valuable public companies: Apple (#1), Alphabet (Google, #2), Microsoft (#3), Amazon (#5), ...
Brainstorm Open Source Software for Neural Networks
NIPS 2016 Symposium on RNNs
Recipient of the 2016 IEEE CIS Neural Networks Pioneer Award (announced in 2015) for pioneering contributions to deep learning and neural networks.
Handwriting Recognition with Fast Deep Neural Nets & LSTM Recurrent Nets (Juergen Schmidhuber)
Switzerland - best country in the world? Leading the world in science, Nobel Prizes, patents, publications, citations, quality of life, competitiveness, happiness, many sports
2011: First Superhuman Visual Pattern Recognition
The formal theory of creativity by Juergen Schmidhuber explains the desire to learn motor skills, to do science, to produce art
Learning Robots
Resilient machine with Continuous Self-Modeling
Statistical Robotics
Best robot car so far (Dickmanns, 1995)
Unsupervised Learning
Attentive vision
STIFF - EU research project on enhancing biomorphic agility of robot arms and hands through variable stiffness & elasticity
The Swiss AI Lab IDSIA
What's new in Juergen Schmidhuber's page?
Master's Degree in Informatics with a Major in Intelligent Systems -  a master's in computer science, with a specialization in Artificial Intelligence
Home Page of Juergen Schmidhuber
Juergen Schmidhuber at Singularity Summit 2009 - Compression Progress: The Algorithmic Principle Behind Curiosity and Creativity and Art and Science
The EU - a new kind of empire?
Juergen Schmidhuber and his iCub baby robot
Juergen Schmidhuber at TU Munich Computer Science
robot population explosion
Deep Learning
AMA (ask me anything)
Lugano, Switzerland
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Update of March 2019: Thanks again for many excellent applications! We have not yet filled all positions. We are not in a hurry, hoping to find people with the profile necessary to complement the already existing expertise. We are also announcing numerous additional job openings, thanks to a big new ERC grant.

Original announcement: Thanks to generous gifts by Google DeepMind and by NVIDIA to Jürgen Schmidhuber's group at the Swiss AI Lab IDSIA, and thanks to a new SNF grant on deep learning-based video analysis, we can now offer additional jobs for postdocs and PhD students. (Recently we had job openings for the related RNNAIssance project.) We specifically invite applications from people with postdoc experience.

We are looking for outstanding candidates with experience / interest in topics such as deep learning neural networks, video analysis, RNNs and Long Short-Term Memory (LSTM), meta-learning or "learning to learn learning algorithms", evolutionary computation, RNN evolution, compressed network search, reinforcement learning (RL) for robots in realistic partially observable environments where traditional RL (for board games etc) does not work, unsupervised learning, curiosity-driven learning and the Formal Theory of Fun & Creativity, hierarchical reinforcement learning, general artificial intelligence, universal learning machines, search for programs running on general purpose computers such as RNNs (see our NIPS RNN Symposium), and "learning to think." (You will also collaborate with other lab members on other projects - we are one big family!)

The general goal is to advance the state of the art in machine learning and AI. Preferred start: Soon. Duration for postdocs: initially for 2 years, with possibility of prolongation.

INSTRUCTIONS: Submit your CV, a brief statement of research interests explaining why exactly you'd like to work with us, and a list of 3 references and their email addresses to (Do not send articles or transcripts or other large files - they will be deleted.) In the subject header, mention your full name followed by the keyword rnnai, and add "PhD" in case of PhD students, or add "postdoc" in case of postdocs. For example, if your name is Jo Mo, and you are applying as a PhD student, use subject: Jo Mo rnnai PhD. As a PhD student, you must also submit your full application to SUPSI through this PHD ONLINE FORM. As a postdoc, you must submit it through this POSTDOC ONLINE FORM. (We might re-open these forms again later).

PhD student salary: Initially CHF 46'000 per year. Standard postdoc salary: CHF 80'000 per year. 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, in Switzerland's first A.I. Master's degree 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 (follow SUPSI, Documenti ufficiali). Official language at IDSIA is English.

The Swiss AI Lab IDSIA was the smallest of the world's top ten AI labs listed in the 1997 "X-Lab Survey" by Business Week magazine. IDSIA's most important work was done after 1997 though. As of March 2017, the four most valuable public companies in the world (Apple, Alphabet/Google, Microsoft, Amazon) are heavily using IDSIA's deep learning algorithms. IDSIA won many international pattern recognition competitions, for example, the first official computer vision contests won by deep CNNs. Its highly cited Ant Colony Optimization Algorithms broke numerous benchmark records and are now widely used in industry for routing, logistics etc (today entire conferences specialize on Artificial Ants). IDSIA is also the origin of the first mathematical theory of optimal Universal Artificial Intelligence and self-referential Universal Problem Solvers (previous work on general AI was dominated by heuristics). IDSIA's artificial Recurrent Neural Networks learn to solve numerous previous unlearnable sequence processing tasks through gradient descent, Artificial Evolution and other methods. In particular, IDSIA's LSTM RNNs are now available to billions of smartphone users, e.g., for speech recognition, or machine translation through Google Translate. Research topics also include complexity and generalization issues, unsupervised learning and information theory, forecasting, learning robots. IDSIA's results were reviewed not only in science journals such as Nature, Science, Scientific American, but also in numerous popular press articles in TIME magazine, the New York Times, der SPIEGEL, and many others. Numerous TV shows on Tech & Science helped to popularize IDSIA's achievements. IDSIA is affiliated with the University of Lugano (USI) and USI's Faculty of Informatics and SUPSI. Many IDSIA alumni went on to become professors. Google DeepMind is heavily influenced by our former students: DeepMind's first PhDs in AI and Machine Learning came from our lab, one of them co-founder, one of them first employee; others joined later. IDSIA is located just outside the beautiful city of Lugano in Ticino (pics), the scenic southern Swiss province. Milano, Italy's center of fashion and finance, is 1 hour away, Venice 3 hours.

Switzerland is the world's leading science nation. It is the origin of special relativity (1905) and the World Wide Web (1990), is associated with 105 Nobel laureates, and boasts far more Nobel prizes per capita than any other nation. It also has the world's highest number of publications per capita, the highest number of patents per capita, the highest citation impact factor, the most cited single-author paper, etc, etc. As of 2016, Switzerland is the world's most competitive country for the 7th year in a row, according to the World Economic Forum. It's also the happiest country (1990s average), according to the Happiness Foundation. More.

Videos of talks by Juergen Schmidhuber
Robot Learning
History of computer vision contests won by deep CNNs on GPU
Artificial Curiosity
Feedback Network
Deep Learning in Neural Networks: an Overview
Our impact on the world's most valuable public companies: Apple (#1), Alphabet (Google, #2), Microsoft (#3), Amazon (#5), ...
Reinforcement Learning
The RNN Book
My first Deep Learner of 1991 + Deep Learning timeline 1962-2013
Subgoal learning
Deep Learning neural nets won the MICCAI 2013 Grand Challenge on Mitosis Detection
Pybrain Machine Learning Library
Evolino for time series prediction
Genetic Programming
SSA learns a complex task involving two agents and two keys
Optimal Ordered Problem Solver
Universal AI
Goedel machine
Theory of Beauty and Low- complexity Art
Randomness and Kolmogorov complexity
Speed Prior
Computing the Universe
videos of talks on deep learning in the US
Juergen Schmidhuber's talks at DLD 2016 - Europe's hottest conference ticket
Juergen Schmidhuber at the International Health Forum 2015. Credits: Wort & Bild Verlag / Eleana Hegerich
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