Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- CNRS
- Inria, the French national research institute for the digital sciences
- Institut Pasteur
- Aix-Marseille Université
- Aix-Marseille University
- CEA-Saclay
- Consortium Virome@tlas
- Ecole Centrale de Lyon
- FRANCE ENERGIES MARINES
- French National Research Institute for Sustainable Development
- IMT - Atlantique
- INSERM U1183
- Institut of Mathematics of Marseille
- Nantes Université
- Nature Careers
- Observatoire de la Côte d'Azur
- University of Lille
- Université Grenoble Alpes
- Université Grenoble Alpes, laboratoire TIMC, équipe GMCAO
- Université Savoie Mont Blanc
- Université de Caen Normandie
- Université de Strasbourg
- École Normale Supéireure
- 13 more »
- « less
-
Field
-
(including computer science, machine learning or deep learning). Activities Description of the research activities : The post-doctoral researcher will develop the research actions defined in his/her research
-
of autonomous mobile machines integrating perception, reasoning, learning, action and reaction capabilities. The team's main research areas are: architectures for autonomous robots, human-robot interaction
-
project combines techniques from machine learning, natural language processing (NLP), and knowledge representation to support legal scholarship and decision-making. The position entails close academic
-
Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 18 days ago
, CIRAD AMAP, CIRAD PHIM, CIRAD PBVMT, INRAE ePhytia, INRAE IGEPP, INRAE LISAH, IRD EGCE, IRD IEES, Univ. Paris Saclay, TelaBotanica). This is a postdoctoral position in Machine Learning, more
-
FieldPhysicsYears of Research ExperienceNone Additional Information Eligibility criteria We are looking for a colleague with a PhD in particle physics. Experience with machine learning and/or experience with
-
and AI to efficiently design safe systems. This is a postdoctoral position in the fields of AI planning, reinforcement learning (RL), and formal methods. The position is initially funded for 12 months
-
of massive galaxies from the primordial Universe to z~2. This project combines a unique JWST dataset with state-of-the art hydrodynamical simulations and machine learning techniques to understand the origins
-
statistics and/or machine learning Specific knowledge • Proficiency in scientific computing • Knowledge of machine learning packages in Python or R • Proficiency in English (minimum level B2), as the postdoc
-
perception for robotics; machine learning. o An interest for approaches based on foundation models. o Proficiency in open-source libraries: Pytorch or equivalent, OpenCV, Open3D, PCL, etc. o Programming
-
that interaction represents the foundation of active learning and fosters acquisition and retention of knowledge, as opposed to passive reception in traditional teaching. Some benefits of MR are now well established