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Electrical Engineering, Computer Science, or a related discipline. A research-oriented attitude. Solid background in machine learning and optimization methods. Knowledge and experience in (wireless
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Foundations: Knowledge of optimization techniques (e.g., LP, CVX, etc), including for/with ML (first order methods, data-driven algorithms, etc). Data Foundations: Hands on experience in data analysis (Python
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and decentralised data-center capabilities to optimize urban performance. This project aims to explore how telecommunications networks and urban infrastructures interdepend and co-evolve, and to
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Knowledge of alternative propulsion systems (hydrogen, electric, hybrid) Familiarity with ATM concepts, airspace design, or traffic flow management Experience with optimization or operational research methods
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optimally for future challenges. This PhD position is part of the SecReSy4You MSCA Doctoral Network, which focuses on developing next-generation methods for security and resilience of cyber-physical systems
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CHP units, the wider energy system risks losing a crucial flexibility resource. Through strategic integration hybrid energy storage systems with greenhouse operations via optimization methods, control
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MRI measurements can be translated into meaningful input for predicting optimal sensor phase configurations and feedback control; Identify pathways towards the integration of domain knowledge about MRI
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other things, cell programming and patterning. Current methods for hormone-induced regeneration in tissue culture often give limited and unpredictable results. Even in optimal conditions only a few cells
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knowledge of the potential of glycoscience in cancer immunotherapy and the necessary transferable skills. CanGoNano will provide an international, intersectoral and interdisciplinary educational program
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support optimization of patient care. Whether this is achievable depends on the reliability of an AI-model. Testing of AI is often done on small numbers, and AI-models are not equally useful in all