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to next-generation 2D gas sensors. You will manage large-scale simulations run on world-class supercomputing facilities alongside AI algorithms and data analytics tools, and share your results with
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algorithms and hardware, including hybrid architectures, as well as related foundational research. The successful candidate(s) will conduct research in theoretical quantum computing and related applications
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to both technical metrics and educational outcomes. Responsible AI and fairness auditing. Conduct algorithmic fairness validation of the CLARA system, develop documentation on data governance and GDPR
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, automated design-space exploration, and cross-technology benchmarking, providing new insights into the co-design of learning algorithms, memory technologies, and neuromorphic hardware architectures for future
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communication and sensing performance. You will design and analyse new algorithms for beam forming, beam focusing, localization, and sensing using XL and distributed reconfigurable antenna arrays. The aim is to
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, focusing on the development of algorithms for proactive decision support in non-stationary warehouse environments. This project aims to study warehouse efficiency across interdependent processes – including
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work to segmentation algorithms with computer scientists. It is a preference if you additionally have experience in performing interdisciplinary research together with another scientific specialty
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(e.g. Agentic Reinforcement Learning), evaluation, tool use, agentic harness, or retrieval-augmented systems. Internship/full-time experience from research, engineering, or algorithm-development roles in
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or communications venues. Interest in mission-critical and critical infrastructure scenarios. What you will do Develop models, algorithms and optimization methods for resilient 6G transport networks, using machine
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investigate suitable topologies, materials, and components to achieve high efficiency and scalability up to 500 kW. Advanced control algorithms will be developed to ensure stable power flow under varying