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PhD Fellow in Anthropology: Bushmeat, Infrastructure and Zoonotic Risk in Africa–China Contact Zones
relations, trade practices, and local perceptions of zoonotic risk. Analyse how roads, mining, urbanisation, and migration influence bushmeat markets and disease risk. Produce a doctoral dissertation aligned
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- Multimodal Perception and Localization for Robots in Extreme Visibility Conditions - Source Localization and Hazard Assessment Using Multisensor Fusion. - Semantic-Based Exploration Strategies for High-Risk
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. Key Responsibilities: Develop and implement perception and control algorithms for robotic arms and embodied AI systems. Assist in integrating multimodal AI models (vision, language, force sensors) with
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. Candidates should demonstrate technical proficiency in one or more of the following areas: Embodied AI and robot learning Vision-language-action (VLA) or multimodal AI modeling Perception, control
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Embodied AI, with a focus on integrating AI-driven perception, reasoning, and action to enable intelligent robotic behavior across diverse real-world environments. The position involves working on embodied
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or more of the following areas is required: Embodied AI and robot learning Vision-language-action (VLA) modeling Perception, control, and interaction for real-world robotic systems Deep learning, multimodal
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AI and robot learning Vision-language-action (VLA) or multimodal AI modeling Perception, control, or interaction for robotic systems Deep learning or applied machine learning for robotics Practical
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–robot interaction and ergonomics Automation and robotised workplaces (industry use-cases) Field robotics and harsh-environment robotics Predictive maintenance, sensor systems, multimodal monitoring AI/ML
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–robot interaction and ergonomics Automation and robotised workplaces (industry use-cases) Field robotics and harsh-environment robotics Predictive maintenance, sensor systems, multimodal monitoring AI/ML
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tactile sensations for 3D interaction. The project ADVHANDTURE aims at introducing an original computational approach for handling multimodal tactile feedback within immersive environments. For that purpose