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ISCApad Archive  »  2017  »  ISCApad #232  »  Jobs  »  (2017-06-06) Post-doctoral Research Associate in Advanced Deep Neural network Architectures for ASR , Univ. of Crete, Greece

ISCApad #232

Tuesday, October 10, 2017 by Chris Wellekens

6-11 (2017-06-06) Post-doctoral Research Associate in Advanced Deep Neural network Architectures for ASR , Univ. of Crete, Greece
  

Department of Computer Science, University of Crete, Greece
Post-doctoral Research Associate in Advanced Deep Neural network Architectures for ASR  (Fixed Term)
 
SALARY: €24000-€28000 per year
CLOSING DATE: 30 June 2017
REFERENCE: ASR1
TO APPLY: Send detailed CV, a motivation letter and 3 major publications to yannis@csd.uoc.gr
 
In the past few years, Deep Neural Networks (DNNs) have achieved tremendous success for many supervised machine learning tasks, including acoustic modelling for Automatic Speech Recognition (ASR). Advanced models such as Convolutional Neural Networks (CNNs) and Long Short Term Recurrent Neural Networks (LSTMs) have contributed to recent empirical breakthroughs. Network depth has played perhaps the most important role in these successes. However, increased depth represents challenges in the optimization of the network and despite the efforts to overcome these challenges some of the optimization issues are still important resistant. Advanced networks such as highway networks and (wide) residual networks seems to offer solutions to these issues.
This position represents an ideal opportunity to work in or move into advanced deep neural networks, as it will involve collaborating widely across academia and industry, and working on one of the most pressing research areas of machine learning for the development of robust ASR systems.
Based in Heraklion Crete the post will be with Prof. Yannis Stylianou and Dr. Vassilis Tsiaras as part of the speech processing group within the Department of Computer Science at the University of Crete. You will explore a rich set of network architectures and thoroughly examine how several different aspects affect the accuracy of ASR. The work will be performed within the framework of advanced deep neural network architectures for various signal processing tasks including 1D and 2D signals. The focus of the post will be to perform various experiments with well-known architectures, explore and suggest modifications, process and reshape knowledge from various signal processing/classification tasks towards speech processing for the purpose of ASR. Outcomes will directly feed into improvements of ASR systems in-house working with state-of-the art ASR tasks (i.e., CHiME4, REVERB, etc) and of our industrial partners using real-life data.
The post involves travel to international conferences and project meetings with our academic and industrial partners. There will be the possibility to co-advise doctoral students and potentially other teaching opportunities.
Applicants should have a doctorate in speech signal processing area for ASR, computer science, applied mathematics or related field and ideally a strong background in deep learning and mathematics. Knowledge of deep learning systems such as Tensorflow or Theano etc and ASR systems like Kaldi are an advantage. Proficiency in computer programming in C and/or Python are expected.
Informal inquiries should be directed to Prof. Yannis Stylianou by email, yannis@csd.uoc.gr
Fixed term: In the first instance, the funding supporting the post is for two years. We are expecting project extension which will provide funding for a further 7-12 months for this post.
Interviews are expected to take place the week commencing 10th July 2017. Expected start date: September 2017, however earlier and later start dates will be considered.
 
To apply, please send detailed CV, a motivation letter and 3 major publications of yours to: yannis@csd.uoc.gr (Prof. Yannis Stylianou)


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