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Villeneuve-d'Ascq, Hauts-de-France INRIA Temps pleinJob Context and RequirementsWe are seeking a highly motivated PhD candidate to join our team at INRIA and work on a project focused on robust reinforcement learning and privacy in sequential decision making. The candidate will be supported by the PEPR project FOUNDRY and supervised by Debabrota and Emilie.As RL algorithms are being deployed in real-life...
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Villeneuve-d'Ascq, Hauts-de-France INRIA Temps pleinJob DescriptionThe postdoctoral researcher will be part of the team at INRIA and will work on understanding the impact of different types of constraints and structures on the performance and design of bandit and RL algorithms.The project aims to simulate existing and new collaborations with researchers and groups working on responsible AI, bandits, and...
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Villeneuve-d'Ascq, Hauts-de-France INRIA Temps pleinContext and Benefits of the PositionThe postdoctoral researcher will be part of the INRIA team and will work under the supervision of Debabrota. The researcher will investigate the impact of different types of constraints and structures on the performance and design of bandit and RL algorithms.The project aims to simulate existing and new collaborations with...
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Villeneuve-d'Ascq, Hauts-de-France INRIA Temps pleinResearch ContextThe selected candidate will be part of the research team at INRIA, working under the supervision of Debabrota. The objective of this postdoctoral position is to investigate the impact of different types of constraints and structures on the performance and design of bandit and reinforcement learning algorithms. This research aims to simulate...
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Villeneuve-d'Ascq, Hauts-de-France INRIA Temps pleinContext and advantages of the positionThe successful candidate will be supported by the PEPR project FOUNDRY and supervised by Debabrota and Emilie, affiliated with the INRIA. The project aims to study the impact of privacy in contextual bandits and MDPs, and to design optimal, computationally efficient algorithms.Main activitiesThe candidate will be...
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Villeneuve-d'Ascq, Hauts-de-France INRIA Temps pleinContext and Key Features of the PositionThe selected candidate will be supported by the PEPR project FOUNDRY and supervised by Debabrota and Emilie, affiliated with the INRIA.As RL algorithms are increasingly deployed in real-life scenarios, questions arise regarding responsible deployment, such as robustness to noise and perturbations in the feedback from...
PhD Researcher in Reinforcement Learning: Robustness and Privacy
Il y a 2 mois
About INRIA and This Opportunity
INRIA is a leading French research institute dedicated to advancing computer science and digital technologies. We are seeking a highly motivated PhD candidate to join our team and contribute to cutting-edge research in reinforcement learning (RL).
Research Focus: Responsible AI through Robustness and Privacy in Reinforcement Learning
As RL algorithms increasingly find applications in real-world scenarios, ensuring their responsible deployment becomes paramount. This PhD position will focus on addressing critical challenges related to robustness and privacy in sequential decision-making.
Key Research Areas:
- Privacy-Preserving Reinforcement Learning:
Investigating the impact of differential privacy on RL algorithms, particularly in complex settings like Markov Decision Processes (MDPs) and contextual bandits. The goal is to design efficient algorithms that preserve user privacy without sacrificing performance.
Robust Reinforcement Learning:Exploring techniques to enhance the robustness of RL agents against noise, perturbations, and adversarial attacks in feedback. This involves developing algorithms that can effectively handle uncertainties and maintain reliable performance in real-world environments.
Project Impact:
This research has the potential to significantly advance the field of responsible AI by providing practical solutions for deploying RL algorithms safely, securely, and ethically. The findings will contribute to building trust in AI systems and fostering their widespread adoption.
Candidate Profile:
- Strong mathematical and statistical background.
- Solid understanding of machine learning, algorithms, and statistics.
- Interest in differential privacy and robustness techniques.
- Proficiency in programming languages such as Python and C/C++.
- Excellent communication and collaboration skills.
Benefits of Joining INRIA:
INRIA offers a stimulating research environment with access to state-of-the-art facilities and resources. You will have the opportunity to collaborate with leading researchers in your field, attend international conferences, and contribute to impactful projects.
