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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
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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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algorithms and simulation models using Python, MATLAB, Julia, or other suitable tools. Analysing simulation and project data, and validating the developed methods through practical case studies. Preparing
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and model export strategies Be a hands-on technologist in the R&D projects linked to control, optimization algorithms/tools to plan the deployment of DERs such as energy storage systems (ESS
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, within the scope of the project, MICROCLI-MAC (1/MAC/2/2.4/0044), “Tecnología y gestión inteligente de microclimas para la adaptación a un clima cambiante en la Macro Región Macaronésica y Terceros Países
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the setup and tuning of active control algorithms. The most successful sensor prototypes are foreseen to be deployed in ETpathfinder seismic filters and could potentially be used for the stable recycling