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the activities of GT3. The initial phases will focus on studying the ideal frameworks for creating the IT platform and developing AI algorithms for data analysis. In particular, the data storage structure will be
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-loss events undermine statistical confidence. The aim is to develop i) edge intelligence (on-turbine smart algorithms for data preprocessing), ii) resilient data movement (error-tolerant, cybersecure
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-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 diagnosis of gas turbines
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Prof. Neil Walton (Durham University, UK). The general aim of this project is to develop throughput-optimal entanglement distribution algorithms (both centralized and decentralized algorithms
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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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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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analyse and develop new, well-founded methods and learning algorithms that extend the boundaries of existing techniques - for example, with respect to expressivity, generalization, interpretability
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of pinching plasmas. This research associate will work with the Michigan State University (MSU) team to develop new scalable algorithms inside of the Parthenon framework, an AMR performance portable framework
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Genomics at Harvard Medical School Several positions are available in the Park Lab (https://compbio.hms.harvard.edu/ ). The aim of the laboratory is to develop and apply innovative computational methods
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algorithmic aspects related to the development of highly accurate, efficient, and robust AI models capable of operating effectively within complex and dynamic radiofrequency spectral landscapes, accounting