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, including a mixture of classical and quantum mechanics simulations, cheminformatics and machine learning, as well as collaborative software development, providing expertise for a broad range of future careers
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simulation results with experimental data. This project will integrate advanced AI techniques, including machine learning for parameter optimisation (e.g., Bayesian optimisation, reinforcement learning), AI
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health. Successful candidates may have experience in electron or X-ray microscopy, image analysis, AI and machine learning, quantitative data science or computational modelling. They will be able to work
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adaptive resource allocation, AI-driven network orchestration, dynamic beam steering, joint communication and sensing, and cross-layer optimization. Machine learning techniques will be investigated
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-trivial software. Solid understanding of algorithms, numerical methods, scientific computing, or machine learning. Ability and motivation to write clean, maintainable and well-tested code. Strong interest
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for recruitment positions for general criteria for the position. Preferred selection criteria Good oral and written presentation skills in Norwegian/Scandinavian equivalent level or acquire them during the course
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% of your time), including tutorials and supervision of Bachelor’s theses. This is what we ask of you This is an interdisciplinary project that combines machine learning and AI, probabilistic risk
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meet the requirements for admission to the faculty's doctoral programme in Engineering Cybernetics . Strong programming skills, in particular Python, and practical experience with modern machine learning
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programming skills in Python; initial experience with machine learning frameworks such as PyTorch or TensorFlow Initial practical experience from a master's thesis, study projects, internships, or open-source
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machine learning and AI, probabilistic risk modelling, hydrology and actuarial science. We realize that candidates will usually have expertise in one of these fields and ask for a genuine interest in the