Sorbonne Université

1 PhD position at Sorbonne University (Paris – France) on “Reinforcement learning models for search-oriented conversational systems”
The thesis with co-supervised by Laure Soulier (MLIA-LIP6) and Ludovic Denoyer (FAIR). We are recruiting for the full-time position of a PhD researcher in the fields of Machine Learning (ML)/Information Retrieval (IR) to join the ANR Project on “Search-oriented conversational systems” (SESAMS).
The candidate will be involved in the design of reinforcement learning models for supporting search-oriented conversational systems. The objective of the thesis is to reverse the information retrieval paradigm based on scoring models to design IR-driven reinforcement  policy by taking into account users’ interactions with search engines and conversational systems.

Working place:
The candidate will be host in Paris (France) in the LIP6 lab in the MLIA team (
The MLIA team at computer Science lab. at Sorbonne, hosts 10 permanent researchers and about 30 PhDs. The lab  is equipped with computer facilities including GPU clusters (>70 GPU cards) required for machine learning and deep learning projects. The PhD students will have a workplace and access to all the facilities of the lab.
Sorbonne University has launched in 2019 a research center on AI (Sorbonne Center on AI). The PhD students
will have access to all the facilities provided by the center.

– Outstanding master‘s degree (or an equivalent university degree) in computer science or another related disciplines (as e.g. mathematics, computational linguistics, information sciences, computer engineering, etc.).
– The candidate should master statistical learning methods, information retrieval and/or natural language processing fields.
– We expect outstanding analytical competence, strong interest in interdisciplinary research (Machine learning/Information retrieval), experience in software engineering (strong programming skills in Python and ML/RL libraries), as well as superior organization and communication skills.
– Fluency in spoken and written English is required.

To apply, please email and with:
– a curriculum vitae, with contact of  2  or more referees
– a cover letter
– a research outcome (e.g. master thesis and/or published papers) of the candidate
– a transcript of grades
– letter of recommendation from previous supervisors or master degree referents

Applications will be processed on the flow and will close at the latest on November 30, 2020.

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