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Offer Description Doctoral Position in Robust Railway Intervention Planning under Uncertainty The Chair of Infrastructure Management, led by Professor Dr. Bryan T. Adey within the Institute
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adversarial learning. Working on an exciting research project focused on developing continual and robust VLMs, you will investigate novel approaches to continual learning, model pre-training and post-training
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Technology, and the PhD student will be positioned in the Esbjerg Energy section. The position is part of the internally funded research project SURGE: Speed-optimized USVs for Robust Guidance and Offshore
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23 Jul 2026 Job Information Organisation/Company UNIOVI Department Oficina de Proyectos Europeos Research Field Computer science Researcher Profile First Stage Researcher (R1) Positions Bachelor Positions Application Deadline 5 Aug 2026 - 23:59 (Europe/Madrid) Country Spain Type of...
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primary regenerative braking. EMBs are highly sensitive to EV harsh operating conditions. This project addresses this challenge by developing AI-based EMB clamping force estimators and robust control
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that explicitly account for drift and open-set contamination. O2: Robust uncertainty estimation: Improve calibration and uncertainty reliability under drift (e.g., ensembles, Bayesian approximations, conformal
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a robust collision avoidance chain for autonomous drones equipped with event-based cameras. The ultimate objective is to bring the algorithmic solution to a mature stage, ensuring robustness
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 2 months ago
, expertise, and powerful computational resources (GPUs & CPUs) of the team. This PhD position is fully funded within the framework of RoGSiLT: Robust and Generalizable Sign Language Translation , a
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Hydroinformatics – Uncertainty-Aware Optimisation for Robust Water Distribution System Operation The PhD candidate will develop uncertainty-aware, model-based multi-objective optimisation methods to support robust
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decisions, as superficial stylistic markers disappear. While current systems achieve high accuracy in controlled scenarios, there is a lack of systematic investigations into how robust they are against