ERC Advanced Grant AlgoRNN:
Jobs for PostDocs & PhD Students
Update of 2020: we hired several excellent researchers,
but still have open
positions for PhD students and postdocs on
the European Research Council (ERC) Advanced Grant on "Recurrent Neural Networks and Related Machines That Learn Algorithms"
(AlgoRNN, compare our NIPS Symposium on this topic).
Recurrent neural networks (RNNs)
are general parallel-sequential computers. Some learn their programs or weights. Our
the first RNN to win machine learning contests,
now used billions of times per day through the world's most valuable public companies, e.g., for speech recognition on over 2 billion smartphones, language translation, etc. Nevertheless, in lots of real-world tasks RNNs do not yet live up to their full potential. Although universal in theory, in practice they fail to learn certain important types of algorithms. This ERC project will go beyond today's best RNNs through novel RNN-like systems that address some of the biggest open RNN problems and hottest RNN research topics including
attention & fast weights,
RNN-based reinforcement learning,
optimal transfer learning,
We have direct access to one of the
fastest supercomputers in the world, with over 5000 GPUs, also based in Lugano, Switzerland.
We are looking for outstanding candidates
with experience in topics such as
deep learning neural networks,
RNNs and Long Short-Term Memory (LSTM),
meta-learning or "learning to learn learning algorithms",
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 through
adversarial neural networks that fight each other in a minimax game,
curiosity-driven learning and the Formal Theory of Fun & Creativity,
hierarchical reinforcement learning,
universal learning machines,
search for programs
running on general purpose computers such as RNNs,
"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.
Duration for postdocs: initially for 2 years, with possibility of prolongation.
We also have
additional job openings with separate instructions
generous gifts by Google DeepMind and NVIDIA (which also
gave us a DGX-1 deep learning supercomputer),
and an SNF grant on deep learning-based
(we have filled positions for the
We don't want to rush it, and will take our time to find excellent collaborators.
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
to the world of AI startups.
There is an opportunity to
participate in teaching courses (in English) on machine learning, in
first A.I. Master's degree program
at the University of Lugano.
Official language at
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 firstname.lastname@example.org.
(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 erc, 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 erc PhD.
We will continually evaluate applications until all positions are filled, which may take a while - we will occasionally update this web site.
The Swiss AI Lab IDSIA
was the smallest of the world's top ten AI labs listed in the
"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 (2011).
Its highly cited
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
Artificial Intelligence and self-referential
Universal Problem Solvers (previous work on general
AI was dominated by heuristics).
Recurrent Neural Networks
learn to solve numerous previous unlearnable sequence processing
tasks through gradient descent,
Evolution and other methods. In particular,
IDSIA's LSTM RNNs are now on billions of smartphones and
used billions of times a day, e.g., for
speech recognition, or automatic translation through Google and Facebook.
Also widely used:
our adversarial neural networks that fight each other in a minimax game.
Research topics also include
complexity and generalization issues,
unsupervised learning and information theory,
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
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
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)
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,
most cited single-author paper,
etc. In particular,
according to The Times (2018), Switzerland
leads the world in AI research in terms of citation impact (although China is the nation that produces the most papers on AI).
As of 2017, Switzerland is the world's most
competitive country for the 8th year in a row, according to the World Economic Forum. It's also the
happiest country (1990s average), according to the Happiness Foundation.
The ERC (since 2005) is of the
which still boasts far more
than any other political entity,
and also (thanks in part to ERC) the largest chunk of
recent high-impact publications, according to
Nature (21 March 2017), which also states that
ERC is "recognized as the best in the world in the way it supports fundamental research."