Sort by
Refine Your Search
-
Category
-
Program
-
Field
-
of Research ExperienceNone Additional Information Additional comments Level of studies required: Master 2 in Human and Social Sciences (anthropology, geography, territorial sciences) Desired experience
-
position is part of the project entitled “Co-evolution between brain and dietary behaviours within the human lineage” (CPJ-HOMININES) and will be supervised by Amélie Beaudet at PALEVOPRIM (UMR 7262
-
fundamental human rights), coordinated in France by Thomas Hochmann (University of Paris Nanterre, IUF). It will focus on questions that affect the legal framework of freedom of expression, for example and
-
2 Jun 2024 Job Information Organisation/Company CNRS Department Institut Pascal Research Field Engineering » Materials engineering Physics » Acoustics Researcher Profile First Stage Researcher (R1) Country France Application Deadline 22 Jun 2024 - 23:59 (UTC) Type of Contract Temporary Job...
-
/she will participate in the management of the project (organization of inter-team seminars in particular) and will act as a link between the different international teams involved in the project
-
2 Apr 2024 Job Information Organisation/Company CNRS Department Institut de Recherche Interdisciplinaire en Sciences Sociales Research Field Sociology Juridical sciences Criminology Researcher Profile First Stage Researcher (R1) Country France Application Deadline 22 Apr 2024 - 23:59 (UTC) Type...
-
applied, on the practices of production, circulation, appropriation, and regulation of human and social science knowledge in an open science regime. OpenEdition Lab offers a host environment, an
-
on AUTOMATICS, SIGNAL, IMAGES, SPEECH, COGNITION, ROBOTICS and LEARNING. Multidisciplinary and at the interface between the human, the physical and digital worlds, our research is confronted with measurements
-
specialized in Technology-Enhanced Learning (TEL) and Human-Computer Interaction (HCI). In particular, SICAL has extensive experience in behavior analysis using multimodal data in different contexts, including
-
[1] and SaulLm-7B [2]). In the case of text generation, a common approach is to align the model with human preferences, either via reinforcement learning [3] or via minimization of a supervised loss [4