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Description SOB/D110/2025/01/GR-7043 1 postdoctoral research position in the scientific project “Structural and algorithmic properties of hereditary graph classes” financed by the National Science Center (grant
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-healing processes in conductive composite materials * development of probabilistic algorithms for damage detection and localization * preparation of reports and presentations on conducted research
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information processing, quantum algorithms, higher-order quantum computing, symmetries and representation theory. Key responsibilities include: 1. Actively conducting scientific research. 2. Presentation and
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of programming languages (Java, Kotlin, Python) and collaborative tools (e.g. GitHub), 5) knowledge of basic algorithms used in machine learning and deep learning, with particular emphasis on image analysis
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, quantum thermodynamics, quantum algorithms, higher-order quantum computing, symmetries and representation theory. About the FENG project The increasing number of interconnected devices has made secure
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develop novel algorithms (Vision Transformers, Self-supervised Learning, Explainable AI, and others) and train machine learning models for cancer images (CT and PET/CT scans). The post-doc position involves
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include creating a semantic repository for storing and indexing tax documents, designing machine learning algorithms to represent data in embedding spaces, and building tools for semantic search
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: research field of study Engineering and technology; discipline environmental engineering, mining and energy for the implementation of the project "Application of artificial intelligence algorithms to control
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, the efficiency and time response of single-photon detectors. Furthermore, EPIQUE will provide new perspectives for the design and the benchmarking of algorithms tailored for photonic quantum computation
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that are selected by the special algorithm elaborated at ICCVS. The first in vitro and in vivo studies are very encouraging, and the team plans to start clinical trials in a few years perspective. More information at