Post-Doctoral Research Visit F/M Postdoctoral position on Theory of Reinforcement Learning and [...]

INRIA; Villeneuve-d'Ascq; Sur place; EUR 35 000 - 55 000; Plein temps

Résumé du poste

Un établissement de recherche de premier plan offre une opportunité passionnante pour un postdoctorant en apprentissage par renforcement et IA responsable. Le candidat idéal aura une solide formation en mathématiques et statistiques, ainsi qu'une bonne connaissance des algorithmes d'apprentissage automatique. Le rôle implique des recherches sur les contraintes non linéaires et dynamiques dans l'apprentissage par renforcement, tout en collaborant avec des chercheurs sur des projets innovants. Ce poste offre un environnement stimulant où les contributions auront un impact significatif sur l'IA responsable et la prise de décision adaptative. Si vous êtes passionné par la recherche et souhaitez faire avancer le domaine, cette opportunité est faite pour vous.

Prestations

Remboursement partiel des frais de transport public

7 semaines de congés annuels + 10 jours supplémentaires

Possibilité de télétravail

Équipement professionnel disponible

Événements sociaux, culturels et sportifs

Qualifications

• Forte expérience en mathématiques et statistiques.
• Connaissance des algorithmes d'apprentissage automatique et par renforcement.

Responsabilités

• Investiguer les questions fondamentales des algorithmes d'apprentissage par renforcement.
• Collaborer à la rédaction d'articles scientifiques sur l'IA responsable.

Connaissances

Mathématiques/Statistiques

Apprentissage automatique

Apprentissage par renforcement

Statistiques

Algorithmes

Langages de programmation (Python, C/C++)

Anglais

Formation

Doctorat en informatique ou domaine connexe

Description du poste

In his / her journey of postdoc, the candidate will be supported by . Debabrota is affiliated with the.

The candidate is expected to work on understanding the impact of different types of constraints and structures on the performance and design of bandit and RL algorithms.

The project is expected to simulate the existing and new collaborations with researchers and groups working on responsible AI, bandits, and reinforcement learning. The candidate will also be part of the.

To be specific, the postdoc will first investigate the fundamental question of reinforcement learning and bandits under non-linear and dynamic constraints and then work in tandem with the PhD working on the related topic to develop constrained RL formulations for robustness, privacy, and unbiasedness in sequential decision making and adaptive testing. For further details, please contact Debabrota by email.

All research activities, that is bibliographical search, proposing original ideas related to the topic of the Ph.D. and developing them, presenting the work in the School seminar, workshops, and conferences. Writing papers in order to get them accepted in the best conferences and journals of our field of research (e.g. ICML, NeurIPS, COLT, IJCAI, AAAI, JMLR). Since the work involves and impacts responsible AI in general, the successful candidate should collaborate in writing scientific articles aiming towards a larger audience.

The candidate should preferably have the following skills:

• A strong background in mathematics/statistics
• A good knowledge of machine learning, reinforcement learning, statistics, and algorithms
• Broad interest in responsible and trustworthy AI
• Knowledge of programming languages such as Python, C/C++
• Some experience with implementation and experimentation (a plus)
• A good command of English

Please follow the instructions given to set up your application file.

In brief, the application of the candidate should include his/her CV, an application letter, (two or more) recommendation letters, and the school transcripts. It is recommended that the candidate contacts Debabrota while preparing the application.

Advantages:

• Partial reimbursement of public transport costs
• Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
• Possibility of teleworking and flexible organization of working hours
• Professional equipment available (videoconferencing, loan of computer equipment, etc.)
• Social, cultural, and sports events and activities