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conditions can be complex and requires adaptation strategies. To overcome these limitations, the RESIL-AV project aims to improve detection accuracy by leveraging a network of heterogeneous sensors. This will
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of these reusable packaging using IoT sensors and deep learning techniques embedded in the sensors. During the preliminary work, neural network models were developed to perform simple tasks using accelerometer data
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The Department of Electronic Systems at The Technical Faculty of IT and Design invites applications for a postdoc in the field of RF Sensing and Anomaly Detection as per 1st Aug. 2026, or as soon as
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industrial partners. More information about the AI RF Sensors group is available at: https://www.es.aau.dk/research/ai-rf-sensors Qualification requirements Appointment as postdoc requires academic
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Change: Leverage high-resolution tactile sensors to handle contacts Impact: Autonomous grasping and manipulation Job description Dexterous manipulation represents one of robotics' most fundamental unsolved
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 16 days ago
Framework Programme? Not funded by a EU programme Reference Number 2026-09948 Is the Job related to staff position within a Research Infrastructure? No Offer Description The postdoc position is part of a
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Start of announcement 10.04.2026 End of announcement 27.04.2026 Institute or department Institute of Carbon Cycle Location Geesthacht Apply now Go to applicant portal We seek a postdoc with interest
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Do you have a PhD in InSAR-Geodesy and are you interested in a postdoc
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3 Apr 2026 Job Information Organisation/Company Université Marie et Louis Pasteur Research Field Engineering Researcher Profile Recognised Researcher (R2) Positions Postdoc Positions Application
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methodologies in urban planning. This PostDoc position focuses on AI-based recommender systems to guide stakeholders in choosing a mobility system design. Specifically, the research builds on RLHF techniques