Postdoctoral scholar position in Machine Learning and Optimization at ETH Zurich

The newly established Learning and Adaptive Systems group at ETH
Zurich ( ), led by Andreas Krause, has an open
position for a postdoctoral scholar. The project involves large scale
active learning and sequential decision making based on
high-dimensional data, and will be carried out in collaboration with
researchers at the California Institute of Technology.

Applicants should have finished, or be about to finish their Ph.D.
degrees. They must have an exceptional background in machine learning
or optimization. Successful candidates need to have a strong track
record of publications at top machine learning, AI or theory
conferences (NIPS, ICML, COLT, AISTATS, AAAI, IJCAI, …) and/or
premier journals in the area (JMLR, JAIR, PAMI, …), and have
experience in at least one of the following areas:
– Active learning
– Online learning / bandits
– Combinatorial optimization / approximation algorithms
– Application of discrete optimization in ML and computer vision
– Sequential decision making under uncertainty / stochastic optimal control
– High dimensional statistics
– Algorithms for large scale probabilistic inference

The initial appointment is for 12 months, with possible extensions up
to 3 years.

Working language at ETH Zurich is English — German is not required.

The salary is highly competitive (among the highest in Europe).

Applicants are requested to send their
– CV incl. publication list
– two strongest publications relevant to this position
– contact information for three recommenders
to Andreas Krause ( krausea(at) ). Review of applications will
start immediately, and continue until the position is filled.