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& Collaboration The successful candidate will work at the interface of machine learning and biostatistics, developing new theory, algorithms, and scalable implementations. By establishing a new class of multi-frame
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complex biological systems. Research Environment & Collaboration The successful candidate will work at the interface of machine learning and biostatistics, developing new theory, algorithms, and scalable
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candidate with a background in SAR/InSAR signal processing and time series algorithms, combined with strong expertise from an application domain that strengthens the group’s current activities. Key
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a PhD student, you will develop state-of-the-art learning and inference methods to detect and characterize anomalous radio behavior and to design algorithms that remain reliable under practical
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-funding from industry and academic partners. You can read more about NICE on https://www.ntnu.edu/nice. Duties of the position Complete the doctoral education until obtaining a doctorate Carry out research
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intelligence over the next five years SURE-AI is a Norwegian AI centre funded by the Research Council of Norway (2025-2030). The primary objective is to create a new generation of algorithms for inference and
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, developing new theory, algorithms, and scalable implementations. By establishing a new class of multi-frame factorization methods, the candidate will be positioned at the forefront of genetic data science
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subject areas include hardware, algorithms, visual computing, AI, databases, software engineering, information systems, learning technology, HCI, CSCW, IT operations and applied data processing
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the next five years. SURE-AI is a Norwegian AI center funded by the Research Council of Norway (2025-2030). The primary objective is to create a new generation of algorithms for inference and decision-making
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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