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the closing date for applications. The applicant must have good programming skills, excellent knowledge of algorithms, numerical methods, and signal processing Mandatory experience and formal training: signal
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the PhD has been awarded at the latest within 5 months after the closing date for applications. The applicant must have good programming skills, excellent knowledge of algorithms, numerical methods, and
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IT environment in Norway, and offer a wide range of theoretical and applied IT programmes of study at all levels. Our subject areas include hardware, algorithms, visual computing, AI, databases
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recognition neural networks (e.g., Tsetlin Machines, Graph Neural Networks, RNNs for time-series causal discovery, XGBoost). AI-driven heuristic search (e.g., genetic algorithms, genetic programming, simulated
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mathematical modelling tools. Excellent knowledge of programming languages such as R, Python, Julia, etc. Familiarity with AI algorithms and Machine Learning Fluent oral and written communication skills in
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mathematical modelling tools. Excellent knowledge of programming languages such as R, Python, Julia, etc. Familiarity with AI algorithms and Machine Learning Fluent oral and written communication skills in
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and application of fast solvers for Maxwell’s equations and nonlinear inversion algorithms that we have already developed in a previous PhD project. In addition to electromagnetic geophysics
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of study at all levels. Our subject areas include hardware, algorithms, visual computing, AI, databases, software engineering, information systems, learning technology, HCI, CSCW, IT operations and applied
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. Material Optimization: Use optimization algorithms to design FGMs that meet demanding performance criteria like fatigue resistance and durability. Systems Integration: Apply a systems engineering approach to
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/Machine Learning (AI-ML) approaches to meeting this challenge. Possible topics include, but are not limited to: storylines for plausible narratives of regional climate change, novel algorithms for rare