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PhD thesis Resource-Aware AI for Next-Generation Networks. The PhD project will investigate resource-aware Artificial Intelligence (AI) mechanisms for next-generation communication systems. The research
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experience and profile MSc in artificial intelligence, statistics, computer science or a related field; Strong background in machine learning and/or statistics; Preferred prior knowledge/experience with
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ever, a major national initiative for strategically motivated basic research, education, and faculty recruitment. The program addresses research on artificial intelligence, autonomous systems, and
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Digitisation and advances in data science, including artificial intelligence (AI), which influence and change all areas of life, have a particular impact on life sciences and health-related sciences. For example
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ever, a major national initiative for strategically motivated basic research, education, and faculty recruitment. The program addresses research on artificial intelligence, autonomous systems, and
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explicitly incorporating these uncertainties through "soft constraints," in order to produce more reliable and relevant simulations. This PhD project is part of task 2.2 "Development of Artificial Intelligence
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Max Planck Institute for Intelligent Systems, Tübingen, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | about 1 month ago
institutions for machine learning, computer vision and robotics, and studying the concepts of intelligence and autonomous behavior in artificial systems at different length scales. The position is ideally suited
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for next-generation (6G) communication systems. The project focuses on integrating Artificial Intelligence (AI) and Machine Learning (ML) capabilities into distributed cloud-edge infrastructures to enable
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solutions for pressing societal challenges (e.g. communication, artificial intelligence, climate protection, health, etc.) through modern electronic & photonic technologies. The work covers the entire
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at the intersection of power systems, artificial intelligence, and sustainability. It offers training in modern energy system modelling, machine learning, optimisation, and data analysis, with applications