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Investigating cyber-physical power system resilience and operation School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof Xin Zhang Application Deadline: Applications
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Ecole Nationale des Ponts et Chaussées (ENPC) | Champs sur Marne, le de France | France | 9 days ago
demonstrated the efficacy of employing machine learning approaches to furnish engineers with a rapid computational asset for structural design and monitoring. Given that numerical models incorporating multi
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Artificial intelligence and machine learning methods for model discovery in the social sciences School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof Robin Purshouse
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: Development of ML-based tools for analysis and engineering protein dynamics PhD enrolment: Czech Technical University in Prague DC14: Machine learning for Empirical Valence Bond (EVB) simulations to engineer
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twins, human-centric systems, robotics PhD-E: Optimizing Images Quality and Deep Learning Methods for Vineyard Disease Detection. PhD grantors: University Padova (IT) & Poznan University of Technology (PL
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, natural language processing (NLP) and machine learning Connected and autonomous vehicles Disaster and natural Hazard assessment and management Discrete element method (DEM) and finite element methods (FEM
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Adaptive Learning in Brain-Robot Interactions School of Electrical and Electronic Engineering PhD Research Project Self Funded Dr Mahnaz Arvaneh Application Deadline: Applications accepted all year
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] Subject Area: Machine Learning Appl Deadline: none (posted 2025/10/06 05:00 AM) Position Description: Apply Position Description Department: Zaven and Sonia Akian College of Science and Engineering (CSE
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materials systems at the molecular level with machine learning. The PhD Student will undertake a study analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for
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systems capable of understanding, learning, and acting in complex, dynamic settings. The team works at the intersection of computer vision, multimodal learning, and robotics to create next-generation