Category: Thèse

We are looking for a PhD student in the context of the European PILLAR project (https://pillar-robots.eu/) aiming at developing a new generation of robots endowed with a higher level of autonomy, that are able to determine their own goals and establish their own strategies.

The thesis focuses on the leveraging of large language models and/or foundation models for planning instructions and actions for robots.

Title: “Leveraging language models and reinforcement learning for generating instructions and interacting with robots”

Supervision:
– Laure Soulier, laure.soulier@sorbonne-universite.fr
– Nicolas Thome, nicolas.thome@sorbonne-universite.fr
– Olivier Sigaud, olivier.sigaud@sorbonne-universite.fr

Location: Sorbonne University, Pierre et Marie Curie Campus, 4 Place Jussieu, Paris, France

Candidate profile:
– Master degree in computer science or applied mathematics, Engineering school.
– Background and experience in machine learning and deep learning. Background in Natural Language Processing and/or Reinforcement Learning is appreciated.
– Good technical skills in programming.

How to apply: please send a cv, motivation letter, grades obtained in master, recommendation letters when possible to laure.soulier@sorbonne-universite.fr, nicolas.thome@sorbonne-universite.fr and olivier.sigaud@sorbonne-universite.fr Start date: October/November 2023

More information: https://thome.isir.upmc.fr/PhD%20PILLAR’23.pdf

A funded PhD position is available in the AIstroSight team, INRIA, Lyon, France (https://team.inria.fr/aistrosight/), starting in November 2023. Our interdisciplinary team aims at developing innovative numerical methods for the search of new drug candidates to treat brain diseases, targeting neurons as well as glial cells. We value diversity, trust, growth, equity and creativity.

Project title: Partial differential equation discovery for spatio-temporal simulations in cells.

The goal of this PhD project is to develop a data-driven partial differential equation (PDE) discovery method for complex dynamical systems such as brain cells. The algorithm will be evaluated on its ability to robustly and accurately learn cell function at the macroscopic scale from data simulated at the nanoscopic level.

See subject details here: https://team.inria.fr/aistrosight/files/2023/06/PDE_Discovery_AIstroSight_2023.pdf

Candidate profile
We are looking for a student with a Master degree who has experience in at least one of the following areas: data science/machine learning/mathematical modeling as well as an interest in cell biology/neuroscience. Proficiency in written and oral English is required. No knowledge of French is needed. Most importantly, we are looking for future colleagues who are eager to learn and grow, and who are driven by scientific curiosity.

If you want to apply, please reach out to thomas.guyet@inria.fr, audrey.denizot@inria.fr, and hugues.berry@inria.fr with a one-page statement presenting your interests and goals, a CV and the contact information of at least 2 referees.

Application deadline: June 26th 2023.

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