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15 Sep 2025 Job Information Organisation/Company Seed Robotics Research Field Computer science » Cybernetics Computer science » Programming Computer science » Systems design Engineering » Control
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We are seeking one enthusiastic and motivated individual to work within the Zero-G AstroLab, School of Engineering, on a project funded by the UK Research and Innovation (UKRI) in planetary defence to protect our planet from asteroid hazards. The aim of the project is to deliver and validate of...
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electromagnetic device performance analysis>>>Embedded SystemsResearch focuses on:•Robotics, computer vision, and machine learning/deep learning•Wearable and implantable sensors, biosensors, and tele
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of Coimbra], hereinafter referred to as RRCPADCT, as well as further applicable legislation, for the scientific area of Electrical and Computer Engineering, subarea of Automation and Robotics
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About the Opportunity This job seeks a research assistant to work on one or more projects related to the development and assessment of wearable robotics. Possible projects topics include: 1
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University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees on performance, safety, and robustness of robotic and learning-enabled systems
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on performance, safety, and robustness of robotic and learning-enabled systems. The research group is seeking a talented Doctoral Researcher in nonlinear systems and control with strong interest in nonlinear
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, Robotics, Computer Science, Statistics, or related discipline. Strong background in Machine Learning and Control Theory. Demonstrated experience in research projects with industrial partners. Excellent
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Carl von Ossietzky Universität Oldenburg | Oldenburg Oldenburg, Niedersachsen | Germany | about 2 months ago
physiological insect navigation data. Modeling navigation neural circuits. Close collaboration with robotics teams. Collaborating with other researchers on interdisciplinary research projects and publications
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University explores synergies between nonlinear control theory and physics informed machine learning to provide formal guarantees on performance, safety, and robustness of robotic and learning-enabled systems