Sort by
Refine Your Search
-
Listed
-
Field
-
machine learning for cybersecurity, current systems remain largely based on pattern recognition and struggle to incorporate contextual reasoning, temporal dependencies, and relationships between entities
-
they are mainly based on predetermined rules of behavior chosen by the designer. More recently, methods derived from machine learning provided impressive results. However most are datadriven, meaning
-
the delivery of wider co-benefits and minimizing costs. The proposed multi-objective approach, based on optimization and machine learning algorithms, is used for defining optimal configurations, including water
-
of: • machine learning • cybersecurity • distributed systems • privacy-enhancing technologies The research will be carried out within the (team name) at LS2N, focusing on trustworthy AI and cybersecurity
-
SUBATECH. The proposed thesis is part of the research activities of the team RAMBO of the RAMBO team (Robot interaction, Ambient systems, Machine learning, Behaviour, Optimization) of the Lab-STICC
-
operational constraints and employee preferences, within rigorous optimization frameworks. Data science and machine learning: experience with data preparation, feature extraction, and preference learning
-
). Require skills Strong background in communication networks and wireless/satellite systems; Knowledge of machine learning and optimization techniques; Experience with simulation tools (Python, MATLAB, ns-3
-
on computer vision and machine learning techniques, that evaluates video recordings of human movements providing them with a normalized score of functional capacity. However, we lack objective information about
-
30 Jan 2026 Job Information Organisation/Company IMT Atlantique Department Computer Sciences Research Field Computer science Researcher Profile Recognised Researcher (R2) Positions Postdoc Positions