Internship: Learning-based Optimisation of Multi-Robot Systems F/M

About NAVER LABS Europe

NAVER LABS Europe is part of the R&D division of NAVER, Korea’s leading Internet portal and a global tech company with a range of services that include search, commerce, content, fintech, robotics and cloud.

The position

With the growing development of robotics services, the problem of orchestrating a fleet of robots (or autonomous agents) under various constraints has recently become a major design bottleneck, especially when seeking to optimise service operations. In the Optimization with Learning team, we are interested in optimising pick-up and delivery services involving robot fleets moving in open (indoor or outdoor) environments. The underlying challenges stem from hard combinatorial optimisation problems, such as multi-robot routing and scheduling under uncertainty.

This internship is related to our research on Neural Combinatorial Optimization for Robot Fleet Management. More information about this research can be found here:
https://europe.naverlabs.com/research/neural-combinatorial-optimization-robot-fleet-management/

At least two broad approaches traditionally address this type of problem, each with its advantages and drawbacks, especially in the face of uncertainty. On the one hand, Reinforcement Learning (and more generally Sequential Decision Processes) attempts to predict the optimal action at any given instant, based on past or simulated experiences. On the other hand, multi-agent planning aims to build optimal plans given a model of the environment.

The purpose of the internship is to:

• explore the space at the intersection of these two traditions and review the existing literature,

• design new learning algorithms that capture the best of both worlds, and

• conduct experiments to evaluate such algorithms on some of our multi-robot service use cases in simulated environments.

About the research team

In the Action group, we develop AI-driven decision-making capabilities that enable embodied agents to safely execute complex tasks in dynamic environments. To achieve autonomy in real-world everyday spaces, robots must learn from their interactions, understand how to best execute tasks specified by non-expert users, and do so in a safe and reliable manner. This requires sequential decision-making skills that integrate machine learning, adaptive planning, and control in uncertain environments, as well as the ability to solve hard combinatorial optimization problems. Our research combines expertise in reinforcement learning, computer vision, robotic control, sim-to-real transfer, large multimodal foundation models, and neural combinatorial optimization to design AI-based architectures and algorithms that enhance robot autonomy and robustness when completing complex tasks in constantly changing environments.

What we're looking for

• Enrolment in a PhD or Master's program in Machine Learning or Computer Science

• Familiarity with Machine Learning for graph data

• Hands-on experience with Python and PyTorch

• Interest in combinatorial optimisation and its applications

• Understanding of Reinforcement Learning and planning is a plus

Practical Information

Start date: As soon as possible
Duration: 6 months

What we offer

• We foster a collaborative environment dedicated to ambitious, multidisciplinary projects that translate advanced research into impactful, real-world solutions, supported by 30+ years of experience in AI and related fields.
• Flexible work/life balance.

• We are an equal opportunity employer that hires based on skills, experience, and merit. We foster an inclusive and diverse workplace where all qualified candidates are considered fairly, regardless of background.

• We’re based in Meylan, close to Grenoble, a city that offers the perfect balance of urban life, cutting-edge research and technology, and spectacular mountain landscapes that provide countless opportunities to relax, recharge, and enjoy the outdoors.

All applications will be carefully considered, even if not all required skills are met. We value diverse backgrounds and the potential of each candidate, and we offer training to support the development of necessary skills.

NAVER LABS, co-located in Korea and France, is the organization dedicated to preparing NAVER’s future. Scientists at NAVER LABS Europe are empowered to pursue long-term research problems that, if successful, can have significant impact and transform NAVER. We take our ideas as far as research can to create the best technology of its kind. Active participation in the academic community and collaborations with world-class public research groups are, among others, important ways to achieve these goals. Teamwork, focus and persistence are important values for us.

 When applying for this position online, please don't forget to upload your CV and cover letter. Incomplete applications will not be considered.

NAVER LABS Europe is subject to French jurisdiction requiring organisations to stipulate that a job/internship is open to both women and men. None of our jobs/internships are gender specific.

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