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project aims to develop advanced control and planning algorithms that enhance robustness and safety, ensuring reliable performance even in the presence of magnetic fields and other uncertain conditions. The
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. Research Environment & Collaboration The successful candidate will work at the interface of machine learning and biostatistics, developing new theory, algorithms, and scalable implementations. By
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of the candidate and the needs of the research center. More specifically, the postdoc will work on the following topics, in collaboration with the rest of the team: Develop and apply evolutionary algorithms
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to integrate large and complex preference datasets with information at individual level, with specific attention to open and reproducible research, e.g., in the development of codes and algorithms. We will focus
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UiA-CERN PhD Position in Multi-robot Mapping and Environmental Data Sharing - Uncertain Environments
representation, efficient transmission strategies tailored to mission requirements, and algorithms for combining data from multiple sources to improve accuracy and visibility. The project will also explore
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project NICE is a center for research-driven innovation (i.e., an SFI ) in which NTNU, the University of Oslo, and key industry players work together towards developing the knowledge and technology required
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technological progress in our increasingly digital, data- and algorithm-driven world. Integreat develops theories, methods, models and algorithms that integrate general and domain-specific knowledge with data
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, finger, and multimodal) under controlled and semi-wild conditions. Develop AI-based algorithms for biometric trust assessment, anti-fraud analytics, and secure onboarding. Lead the deployment and
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, towards a common goal of transforming the diagnostics and preservation of cultural heritage by developing innovative non-destructive evaluation techniques and advanced digital tools for diagnostics