PhD position in machine learning at ETH Zurich, in collaboration with Microsoft research

Applications are invited for a PhD position focusing on the development of generative probabilistic graphical models for modelling complex data such as text and images. This position is part of a joint collaboration between the Institute of Machine Learning at ETH Zurich and Microsoft Research. This is a unique opportunity for a PhD student to be co-supervised by one advisor from ETH Zurich and one from Microsoft Research in Cambridge UK. The student is expected to take advantage of the opportunities offered by both organizations and to actively seek cross-group collaborations.
The core of the research we would like to pursue is related to the use of generative probabilistic graphical models to describe how text and image data is generated. Although these models are theoretically well understood and in principle provide an optimal approach to inference and learning from data they are often computationally intractable. As a consequence, they are often inferior in predictive performance, when compared to current state-of-the-art deep learning approaches. It is thus a natural question to ask, whether one can combine the benefits of deep learning with those of probabilistic models. This will be the core of the research addressed by the chosen candidate.
The primary location for this position is Zurich but the chosen candidate is expected to spend time at the Cambridge site as well. Fellowships will be remunerated through employment contracts, subjected to the rules of ETH Zurich. All PhD fellows will register as graduate students at ETH Zurich and - upon successful completion of their PhD project - be granted a doctoral degree by ETH Zurich. Details of this process are governed by ETH regulations and committees. The deadline for applications is September 31, 2016. The selection interviews will take place in September and October at ETH Zurich. The expected starting date is January 2017.
We expect admission to be highly competitive. We encourage applications from outstanding candidates with academic backgrounds in Mathematics, Physics, Computer Science and related fields, and a keen interest in doing research in areas like: graphical models, generative models and deep learning. We seek to increase the number of women in areas where they are underrepresented and therefore explicitly encourage women to apply. Furthermore, we are committed to increasing the number of individuals with disabilities in our workforce and therefore encourage applications from such qualified individuals.
For further information please see http://www.da.inf.ethz.ch/ or contact sabrina.nepozitek-AT-inf.ethz.ch.
We are looking forward to receiving your application including CV, a short mission statement and scanned transcripts. Send your application to sabrina.nepozitek-AT-inf.ethz.ch.