Applied Scientist in Optimization
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.
To support this ambition and continue developing our activities, we are looking for a research engineer to join the Machine Learning and Optimization group. One of our research interests is to build innovative solutions that help people seamlessly navigate the physical world, taking into account uncertainties inherent to user's behavior and environment.
Excited about research and its applications, the successful candidate will contribute to the development and benchmarking of novel optimization algorithms. She/he will also participate in their deployment in a number of NAVER products and services.
- M.Sc. or Ph.D. in computer science or operational research
- 3+ years of experience in development of complex algorithms
- Strong coding skills, preferably in python, C/C++ and rust
- Experience in code analysis and optimization for speed/memory consumption
- Operational research and optimization algorithms
- Knowledge of professional software engineering practices
- Working knowledge of Docker and Elastic Search
- Curious, good team player and autonomous
NAVER LABS Europe has positions, Ph.D and PostDoc opportunities throughout the year which are advertised here and on international conference sites that we sponsor such as CVPR, ICCV, NIPS, EMNLP etc. Internships are posted on a separate page.
The 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, data analytics, natural language processing, ethnography and UX working together to create next generation ambient intelligence technology and services that deeply understand users and their contexts.