Master/PhD Internship - Deep Machine Reading

 

NAVER LABS Europe's mission is to advance the state-of-the-art in
Ambient Intelligence, while paving the way for these innovations into
a number of NAVER flagship products and services. This includes
research in models and algorithms to give humans faster and better
access to data and to allow them to interact with technology in
simpler and more natural ways.

In this context, the field of Machine Reading has recently emerged as
a possible continuation of the tasks of Natural Language
Processing. Given a large set of passages of text associated with
questions and answers, our goal consists of learning a question
answering system solely from these examples. As research groups
dedicated to Machine Reading around the globe have started to produce
encouraging results, this task challenges our current understanding of
deep learning and machine comprehension.

In this internship, the successful candidate will be involved in the
design and development of novel models for machine comprehension
applied at the scale of NAVER in the context of electronic
encyclopedia and social media understanding. Finally, at NAVER LABS we
encourage participation in the academic community. Our researchers
collaborate closely with universities and regularly publish in venues
such as ACL, EMNLP, KDD, SIGIR, ICML and NIPS.

Requirements

- Master and/or Ph.D. in machine learning with a strong interest in
    Deep Learning.

- Knowledge of statistical and deep learning application to NLP.

- Strong development skills of relevant frameworks like pytorch and/or
  tensorflow.

References

    Gated End-to-End Memory Networks , Fei Liu and Julien Perez, EACL
    2017
    
    Dialog State Tracking, a machine reading approach using memory
    networks , Julien Perez and Fei Liu, EACL 2017
    
    ReviewQA: a relational aspect-based opinion reading dataset ,
    Quentin Grail and Julien Perez, CAP'2018

Start Date ASAP
Duration 6 months minimum

Application instructions

To submit an application, please send your CV, cover letter and the
names of at least two references to julien.perez@naverlabs.com and
dl_candidates@naverlabs.com