Research scientist in search and recommendation (multiple positions) - Naver Labs Europe
NAVER LABS Europe
Published
25 November 2020
Location
Meylan, Grenoble, France, France
Category
Start date
ASAP

Description

At NAVER LABS, we are inventing the next generation of search and recommendation engines, which have to be multi-modal, multi-stakeholder, unbiased and transparent.

We are looking for applications from research scientists, at the junior or senior levels, to join the Search & Recommendation team. 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 and gives us the chance to see millions of users potentially benefiting the outcomes of our research.

At the same time, we encourage participation in the academic community. Our researchers collaborate closely with universities and regularly publish in venues such as SIGIR, ECIR, RecSys, KDD, NeurIPS, ICML, ACL, and EMNLP.

Required skills

- Ph.D. in Information Retrieval (IR), Recommender Systems (RS) or machine learning (ML)
- Good publication record in top-tier IR, Recommender Systems or Machine Learning conferences.
- Strong development skills, preferably in Python and knowledge of deep learning frameworks
- Experience in particular with sequential decision making under uncertainty, graph neural networks, conversational search or counterfactual reasoning is a plus

Application instructions

You can apply for this position online. Don't forget to upload your CV and cover letter 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.

NAVER 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 technology and services that deeply understand users and their contexts.

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