Researcher in Deep Learning and Reinforcement Learning (multiple positions) ​ - Naver Labs Europe
    27 March 2019
    Grenoble, France
    Job Type


    The mission of NAVER LABS Europe is to advance the state-of-the-art in Ambient Intelligence including autonomous vehicles, robotics, AI, 3D mapping and AR while paving the way for these innovations into NAVER products and services. To implement our current expansion in Europe, we are looking for applications from research scientists who want to contribute to the invention, development and benchmarking of Deep Learning and Reinforcement Learning technologies in diverse areas of sequential decision making such as autonomous navigation, robotic control, Active SLAM, recommendation systems, web search and Human-Computer Interaction.

    At NAVER LABS, we encourage active participation in the academic community and our researchers regularly collaborate with world-class public research groups. We regularly publish in venues such as NeurIPS, ICML, ICLR, ECML and IJCAI. We also release datasets for public use and co-organise challenges such as DSTC-6.

    Required skills

    - Ph.D. in Statistical Machine Learning with a strong experience in Deep Learning and/or Reinforcement learning.
    - Excellent publication track record in major machine learning conferences and journals.
    - Strong development skills, preferably in python and C/C++.
    - Highly motivated.

    Application instructions

    You can apply for this position online (see below). Don't forget to upload your CV, cover letter and the name of at least one reference before you submit.
    Incomplete applications will not be accepted.

    About NAVER LABS

    NAVER LABS Europe has full-time positions, PhD and PostDoc opportunities throughout the year which are advertised here and on international conference sites that we sponsor such as CVPR, ICCV, ICML, NeurIPS, EMNLP etc. NAVER LABS Europe is an equal opportunity employer.

    LABS are in Grenoble in the French Alps. We have a multi and interdisciplinary approach to research with scientists in machine learning, computer vision, artificial intelligence, natural language processing, ethnography and UX working together to create next generation ambient intelligence technology and services that deeply understand users and their contexts.

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