Role overview
We’re looking for an experienced researcher to join the team and contribute to the following research activities:
- Lead research projects on machine learning approaches for sequential decision making and combinatorial optimization.
- Identify and formulate impactful research problems inspired by real-world robotics applications.
- Develop new models and algorithms, for example using deep reinforcement learning, graph neural networks, or other learning-based optimization techniques.
- Design and oversee the implementation of prototypes and proof-of-concept systems to evaluate new approaches.
- Play a leading role in communicating research results, including publications in top-tier conferences and journals.
- Collaborate with researchers and engineers across NAVER LABS to transfer and demonstrate developed approaches on real robotic systems.
- Mentor and collaborate with junior researchers and research engineers.
- Contribute to the visibility of the team through publications, talks, and collaborations.
What we're looking for
- Experience with deep reinforcement learning, in particular multi-agent reinforcement learning.
- Experience with machine learning for structured data, such as graph neural networks or related approaches.
- Experience with combinatorial optimization, neural combinatorial optimization, or learning-augmented optimization methods.
- Demonstrated ability to identify and formulate impactful research problems.
- Experience mentoring students, interns, or junior researchers.
- Strong publication record in leading conferences in machine learning, artificial intelligence, optimization, or robotics (e.g., NeurIPS, ICLR, ICML, AAAI, IROS, ICRA).
- Experience building collaborations across teams or disciplines.
- Interest in connecting machine learning research with real-world applications, in particular in robotics systems.
Tags & focus areas
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