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Field
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) modules into safety-critical embedded systems (autonomous vehicles, drones, industrial and medical devices) raises major safety and security concerns. These modules, often based on deep neural networks
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analysis of control algorithms for autonomous and cyber-physical systems, including nonlinear and hybrid dynamical systems, with stability and performance guarantees. Design and implementation of control
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LVLMs for autonomous driving. Objectives Design, develop, and evaluate novel method(s) to detect and localize hallucinations in LVLM outputs for autonomous driving tasks Investigate and propose mitigation
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of Electronic Systems at The Technical Faculty of IT and Design invites applications for a PhD stipend in the field of Safe Learning Based Control for Autonomous Robots in Dynamic Environments within the general
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About the ProjectProject details Self-adaptive and autonomous systems are increasingly deployed in dynamic and uncertain environments, where effective decision-making relies on accurate models
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-year PhD position at the Faculty of Engineering in fundamental research on risk assessment and decision support for autonomous systems. The position is funded by the ERC AdG Breach , and will focus both
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-build projects, insight or previous experience in third-party funding acquisition are advantageous Above-average commitment High degree of independent and autonomous work High degree of responsibility
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Research theme: Control Engineering, Robotics How to apply: https://uom.link/pgr-apply-2425 UK only This 3.5-year PhD studentship is open to Home (UK) applicants. The successful candidate will
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need for reliable and autonomous offshore infrastructure inspection and surveillance. The project integrates unmanned aerial vehicles (UAVs), unmanned surface vehicles (USVs), and unmanned underwater
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representation. The research will be conducted within the Robotics and InteractionS team at LAAS-CNRS, a historically renowned research environment for Human–Robot Interaction and autonomous robotics. The project