Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Aalborg University
- NTNU - Norwegian University of Science and Technology
- Inria, the French national research institute for the digital sciences
- Norwegian University of Life Sciences (NMBU)
- ARDITI - Agência Regional para o Desenvolvimento da Investigação Tecnologia e Inovação
- Aalborg Universitet
- CNRS
- Cranfield University
- Delft University of Technology (TU Delft)
- Instituto de Engenharia Mecânica
- Kaunas University of Technology
- NTNU Norwegian University of Science and Technology
- Norwegian Institute of Bioeconomy Research
- University of Birmingham
- University of Lund
- University of Nottingham
- University of Sheffield;
- 7 more »
- « less
-
Field
-
-efficient drone platform components integrated with multi-modal sensors and nanogenerators’. Why is the proposed project relevant? Diverse drone platforms (ground/aerial/marine robotic vehicles
-
Inria, the French national research institute for the digital sciences | Talence, Aquitaine | France | 2 months ago
the Auctus team at the Inria center of the University of Bordeaux (Talence). Thisthesis falls within the scope of the team'sscientific axis on the design and control of robotic systems. The project will
-
Robotic-human Orchestration with Wearables for manufacturing: Twin Transition Through Tactile Teaming. As a PhD researcher, you will contribute to the development of a wearable co-pilot system for assisting
-
dynamics, control algorithms and sensor integration can be designed as a coherent system to improve speed, range, maneuverability, response time and operational robustness while also having underwater
-
. Thus a background in fluid mechanics (marine hydrodynamics or aerodynamics) is required. Knowledge of measurement technology and relevant sensors, as well as industry experience from the industry
-
. Automation tools such as social robots, chatbots, sensor systems, and automated documentation and scheduling promise to increase efficiency, support independent living and relieve pressure on care systems
-
—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
-
predictive maintenance of ships and maritime systems. Modern vessels generate large amounts of heterogeneous operational data from sensors, machinery, control systems, maintenance records, and other sources
-
lipid fermentations by integrating data from online spectroscopy, standard bioreactor sensors, and lab-scale bioreactor experiments across various oleaginous microorganisms. The candidate will build and
-
conceptual and practical research using drone detection systems, interceptor drones and other technologies driven by advanced sensors, data communication systems, and artificial intelligence. Are you motivated