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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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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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, 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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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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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
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collaborators 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
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crystalline materials is often responsible for improved materials performance, but it is commonly overlooked in computational materials design. In this project, we will focus on developing accelerated