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twins, optimization, and control. In this PhD project, you will develop a new systems and control theory for learned operators, bridging modern scientific machine learning with classical control theory
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innovative solutions for future communication networks and sensing-enabled services. Job description The successful candidate will contribute to research on energy-efficient network design, optimization, and
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to contribute to high-tech applications, state-of-the-art modelling or experimentation of advanced sustainable materials across the scales? We are looking for outstanding and enthusiastic PhD candidates, with a
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Cities and Crowd Digital Twin Preferred Qualifications : Master’s or PhD degree Effective writing and communication skills Strong publication record Ability to work independently Ability to work with
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TensorFlow. The successful candidate will be able to develop, implement, test, troubleshoot, and optimize AI/ML solutions; automate analytical workflows; investigate complex computational or system issues
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30th September 2026 Languages English English English We are looking for a PhD candidate in Structure-preserving Generative Modeling Apply for this job See advertisement This is NTNU NTNU is a broad
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optimization models for electric vehicle fleet charging planning. Activities: • Apply operations research methods (linear and mixed-integer programming, dynamic optimization, stochastic optimization) • Integrate
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critical for achieving power-efficient operation, programmability, high linearity and low-noise signal conditioning including optimal dynamic range and bandwidth utilization. This position offers a unique
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-scale conditions and evaluate recycled bio ashes as a source of nutrients or growth-promoting components. The research will optimize cultivation and exposure conditions, quantify metal uptake by
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, by that enabling improved control and optimization. Stall detection will be a natural part. The PhD project is internally financed but will be associated to two large research programmes at NTNU and