Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
, suggesting that some physics underlies the fault network patterns (Perrin et al., 2016). Scientific objectives and methodology The project FAILLES aims at developing innovative AI algorithms capable to detect
-
accumulation within the crust, coseismic slip on faults during earthquakes, and postseismic deformation due to the response of the Earth‘s lithosphere to the redistribution of stress after earthquakes
-
, localization, identification of faults, and failure prediction) and reconfiguration or adaptation procedures (reconfiguration of control or objectives, fault-tolerant control) in the event of a detected failure
-
detection and isolation when required. Research Objectives The successful PhD candidate will work on: Data-driven nonlinear control under uncertainty Developing control strategies based on practical feedback
-
PhD fellowship (R1) to work on the MSCA project SAILING. The tasks to be carried out will be focused on developing a fault location and detection on the electrical and communication networks (including
-
will develop and evaluate fault detection and fault location algorithms for these systems. The project is funded by GE Vernova under a wider collaboration with Imperial College London. You will be co
-
, and coverage. Adjust equipment to ensure quality and color match to digital proofs. Monitor and respond to error, alert, or fault messages on automated press operation systems. Load and feed paper
-
PhD fellowship (R1) to work on the MSCA project SAILING. The tasks to be carried out will be focused on developing a fault location and detection on the electrical and communication networks (including
-
Number BI|2026/886-Project ACHILLES– refª 101189689 Is the Job related to staff position within a Research Infrastructure? No Offer Description Public notice for one research grant Refª BI|2026/886 Project
-
: Modern machine learning approaches are increasingly exploited to automate and optimize fault detection and classification. We propose to investigate methods that improve diagnostics under under-represented