At NAVER LABS, we consider that human-centric search and recommendation interfaces are key to enabling a world of Ambient Intelligence. In this new world where location and context are understood, digital technologies will proactively propose and recommend activities, places and things to people, helping them interact and navigate in the physical environment. Such digital recommendation and guidance should be as seamless and natural as possible. The main objective of the Search and Recommendation team at NAVER LABS Europe is to translate this ambition into the design of context-aware, personalised and anticipatory search and recommendation modules.
We’re looking for applications from research scientists at a senior level to join the Search & Recommendation team. Our main research themes are articulated around the development of novel Interactive Machine Learning techniques for dynamic adaptive Search and Recommendation systems. We’re targeting large-scale on-line applications in a variety of domains such as Ambient Intelligence, News Recommendation and Multimodal/Multilingual Search, with a particular attention to FAT (Fairness, Accountability and Transparency) aspects. We are also working on new user interfaces, mixing voice, gesture, text and image, to enrich the range of human/machine feedback.
Our research is carried out with the ‘NAVER’ search group who run the world’s 5th biggest search engine. This provides research opportunities that go far beyond the traditional Information Retrieval framework.
We encourage participation in the academic community. Our researchers collaborate closely with universities and regularly publish in venues such as ACL, EMNLP, KDD, SIGIR, ECIR, ICML and NeurIPS.
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.