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

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