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Field
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learning algorithms. Collaborating with industry partners to understand operational requirements and developing AI pipelines for analysing visual and sensor data collected during inspection processes
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, and machine learning. The successful candidate will support the Principal Investigator (PI) in conducting high-quality research through algorithm development, numerical simulations, and scientific
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include theoretical results, mathematical proofs, and computational algorithms, as well as open-source software and validation through simulations and analysis. Experimental demonstration is an option if it
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Start Date: 26/06/2026 Apply AI/ML models and screening algorithms for the accelerated design and structural discovery of novel porous materials (e.g., MOFs/COFs); Conduct laboratory synthesis, activation
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public service. Job Description The Research Assistant will support the development and implementation of machine learning algorithms for cyber-physical attack detection in electric power systems
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analytical tasks, which have the clinical value in the real-world employment. • Developing novel models and algorithms for 2D or 3D medical vision tasks, such as surgical scene segmentation, depth
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demonstrations. The successful candidate will work at the intersection of multi-disciplinary modelling, advanced AI algorithms, and decision-support tool development. Responsibilities will include programming
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analytical tasks, which have the clinical value in the real-world employment. • To develop novel models and algorithms for 2D or 3D medical vision tasks, such as surgical scene segmentation, depth
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the correctness, robustness and reliability of deep neural networks and AI-enabled software systems. Job Responsibilities: Develop novel methods and algorithms for the verification, testing and robustness analysis
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is part of the Faculty of Medicine and Health Sciences at NTNU. It was established as a Centre of Excellence in 2002, 2012, and again in 2023. Our Centre of Excellence, the Center for Algorithms in