Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- CNRS
- Inria, the French national research institute for the digital sciences
- Aix-Marseille Université
- Institut Pasteur
- Nantes Université
- Nature Careers
- Université Claude Bernard Lyon 1
- Université de Bordeaux / University of Bordeaux
- Aix-Marseille University
- Consortium Virome@tlas
- Ecole Centrale de Lyon
- FRANCE ENERGIES MARINES
- French National Research Institute for Sustainable Development
- IMT - Atlantique
- IMT Mines Albi
- INSERM U1183
- Institut of Mathematics of Marseille
- Observatoire de la Côte d'Azur
- Universite de Montpellier
- University of Lille
- Université Grenoble Alpes
- Université de Caen Normandie
- Université de Strasbourg
- École Normale Supéireure
- 14 more »
- « less
-
Field
-
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 | Rennes, Bretagne | France | 24 days ago
Cancer Research Center. The team has access to several computing facilities (e.g. IGRIDA cluster) and established collaborations with other Inria/Irisa research teams in the field of machine learning. Our
-
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
-
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
-
), whose objective is to extend the HLA-Epicheck model, originally developed within the framework of a PhD thesis, and to implement new deep learning approaches to assess donor–recipient compatibility in
-
scienceEducation LevelPhD or equivalent Skills/Qualifications PhD in computer science Background in probability, Markov chains, MDPs Knowledge about reinforcement learning and planning are a plus but not necessary
-
. • Strong knowledge of signal processing methods and machine learning. • Familiarity with regulatory and ethical constraints in research involving sensitive data. • Ability to work closely with
-
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
-
resonance spectroscopy, imaging (MRI), Applied Mathematics or Machine learning. We are looking for talented, highly-motivated experimentally skilled young scientists with Master degrees or equivalent or PhD
-
relevant to the project's theme and activities. Solid experience in molecular simulation and/or machine learning is required, along with a good knowledge of associated theoretical tools (experience in