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- University of Oslo
- NTNU Norwegian University of Science and Technology
- NTNU - Norwegian University of Science and Technology
- UiT The Arctic University of Norway
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- NORCE Norwegian Research Centre
- University of Bergen
- University of South-Eastern Norway
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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 factorization methods
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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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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 decision-making by pushing
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, please see: http://www.mn.uio.no/ifi/english/research/groups/ltg/ The successful applicant will benefit from close collaboration across disciplines and access to diverse application areas through the joint
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advantage. Language requirement: Good oral and written communication skills in English English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements: https
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information at individual level, with specific attention to open and reproducible research, e.g., in the development of codes and algorithms. We will focus on devising computational solutions that can
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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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algorithms, benchmarking, model selection and evaluation workflows is an advantage Language requirement: Good oral and written communication skills in English English requirements for applicants from outside
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without a master’s degree have until June 30, 2026 to complete the final exam. Desired qualifications: Experience with data simulation, clustering algorithms, benchmarking, model selection and evaluation
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algorithms for parallel/distributed AI/ML Hardware-aware and resource-efficient partitioning for parallel/distributed AI/ML Optimization of process-to-process communication in parallel/distributed AI/ML