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be responsible for carrying out research with the main duties including: development of a crop mapping algorithm computed on super-resolved Sentinel-2 images; develop an automated pipeline to integrate
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Responsibilities Participate in the research project to design a mobile DC microgrid controller for military tactical applications. Develop control algorithms for dynamic master selection, coordinating BESS, PV
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Engineering or related fields. - A solid background in electric power systems is required, as well as experience in the development of optimization algorithms and intelligent systems. - The ability to apply
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and limited resources (fleet size, mobile and fixed charging infrastructure). This project aims to address these challenges by developing novel mathematical models and algorithms to support real-time
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intelligence algorithms, capable of warning far- mers in order to enable early and appropriate interventions. The proposed solution relies on the use of several complementary technologies : • Cameras
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training datasets; Design and carry out laboratory experiments to produce representative experimental training data; Develop physics-informed machine learning algorithms, trained on both numerical
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staff position within a Research Infrastructure? No Offer Description The selected candidate will develop innovative and efficient resource optimization algorithms, suitable for this context, with cost
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | about 1 month ago
research, development, and innovation centre active in the fields of High-Performance Computing (HPC), Data Analytics (HPDA), Artificial Intelligence (AI), and Quantum Computing (QC) and their applications
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produce software implementations of the algorithms developed in this project. About you The University values courage and creativity; openness and engagement; inclusion and diversity; and respect and
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will be as a researcher in a two-year project carried out in close collaboration with our industry partner. The goal is to develop methods for an ML-based decision support system for monitoring and fault