PhD Candidate in Machine Learning

WorkplaceZurich, Zurich region, Switzerland


The Institute for Machine Learning at ETH Zurich is partnering with CSEM for exploring exciting cutting edge research for modelling temporal processes. CSEM is a private research, technology and innovation center specializing in microtechnology, microelectronics, system engineering and renewable energy systems. It offers its customers and industry partners custom-made innovative solutions. The Robotics & Automation group of Center Alpnach is currently looking for a:

In recent years the popularity of machine learning methods has increased dramatically. CSEM has a long experience in this field with technologies that have now reached the market. Huge advancements have taken place in image analysis and natural language processing. In particular the usage of Recurrent Neural Networks has reported ground breaking results in natural language processing. The application of RNN methods has so far been mainly concentrated in audio signals, and the field of multi-dimensional data and temporally correlated image sequences are exciting new areas of research. Modelling temporal processes can offer new insights in to problems in Industrial Production, Remote Sensing and Earth Observation. This thesis project will develop methodologies for modelling multi-dimensional time-based data sets using neural networks.
The work of the PhD candidate will revolve around the design of appropriate model architectures and efficient training methods. The candidate will have the opportunity to explore a variety of data sets with direct industrial applications while working in close contact with the Institute of Machine Learning at ETH Zurich and R&D divisions at CSEM to drive the research toward practical industrial needs. Your responsibility will also include to disseminate and report your results using international platforms and take active part in the activities of the Robotics and Automation group and the Institute of Machine Learning at ETH Zurich.

You have a master degree in Computer Science, Mathematics, Physics or related fields; solid programming skills; good written and spoken English; strong team-working abilities and excellent communication skills. You are enthusiastic, proactive and autonomous. Former experience with neural networks in particular with RNN and experience in computer vision and signal processing are a plus.

In your application, please refer to
and reference  JobID 38732.

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