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Field
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of the sensors under various conditions (laboratory and real-world environments), together with the implementation of machine-learning algorithms for data processing, clustering, and quantification of target
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Max Planck Institute for Intelligent Systems, Tübingen, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | about 1 month ago
computer vision algorithms into the NICE Toolbox. Assist with testing, evaluation, and optimization of implemented computer vision methods. Provide basic user support for researchers using the NICE Toolbox
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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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fields (e.g. interpolation, climatological fill, ML-based gap-filling). • Apply noise-removal algorithms (e.g. signal filtering, radar clutter suppression, spike detection) across sensor and remote
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Wideband Antenna Arrays is performed. The tasks associated with this project involve, but are not limited to, Sensor node hardware design and antenna evaluation RFSoC-based multichannel acquisition and
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robots and sensor networks increasingly use federated learning (FL) to train shared models across many devices without centralising raw data. In realistic deployments, however, each robot experiences
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/FMV, geospatial and AIS tracks, signals and sensor data, and text-based intelligence reports and develop pipelines, annotation frameworks, and quality assurance processes while gaining deep exposure
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learning algorithms, building thermal image mosaics, collecting and analyzing thermal datasets, and contributing to research on PV health monitoring. Applicants should have a bachelor's degree in Computer
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Dipartimento di Ingegneria dell'Informazione - Università degli studi di Padova | Italy | 2 months ago
. The objective is to define robust, scalable theoretical and algorithmic tools applicable to complex and interconnected systems such as smart grids, sensor networks, multi-robot systems, and cyber-physical
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, characterization, optimization, and autonomous decision-making. Advance Bayesian optimization, active learning, machine learning, scientific models, genetic algorithms, and AI agents in physical laboratory systems