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intelligence, RF engineering, and spectrum sensing, with a core focus on AI-based spectrum monitoring for anomaly detection and identification. Your primary responsibilities include developing and evaluating
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Solution project " ASMADI - AI based Spectrum Monitoring for Anomaly Detection and Identification" to develop signal processing algorithms that enable autonomous detection, classification, and filtering
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of the position is two years. Your work tasks The main task of this postdoc position will dedicate on research and development of advanced process control augmented by some AI techniques, e.g., using reinforcement
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, and ethical commitments. The postdoc will contribute to developing a theoretical framework for design, bridging material practices, social interdependence, and long-term resilience. This work could
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to efficiently transmit and analyze high-frequency, high-velocity multimodal data streams, thereby enabling monitoring of offshore wind turbines. Your role will be to contribute to these uses cases by developing
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machine learning models directly on these edge devices for real-time anomaly detection and identification. You will develop robust signal acquisition and processing pipelines, translate research-grade
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for a two-year postdoc, ideally starting August 1st, 2026. The position will encompass the ethnographic study of wind energy infrastructure development in Norway. The postdoc is part of the Sapere Aude
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with natural language. The successful candidate will develop and test novel user interfaces that integrate state-of-the-art Large Language Models (LLMs) with novel logic-based multi-robot planning
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, classifying, and filtering RF signals in real-time on satellites and drones. The key responsibility of the position is to develop custom measurement platforms from discrete hardware components. The role
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several innovative and unconventional collaborations have been and are developed through interdisciplinary co-operations. Thereby, as an employee at the department you will become a part of an international