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PhD in Advanced Testing, Modelling, and Simulation of Composite Materials under High Velocity Impact
for a better world and solutions that can change everyday life. Department of Structural Engineering We teach mechanical engineering, engineering and ICT, and civil and environmental engineering. The
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we will draw up a career plan that includes the skills and knowledge you will acquire An inclusive working environment with ambitious colleagues The opportunity to take Norwegian language courses
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for the position. Preferred selection criteria Experience with machine learning and neural networks Basic knowledge of MR physics Experience with signal processing and/or image processing Experience with Linux
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IT programmes of study at all levels. Our subject areas include hardware, algorithms, visual computing, AI, databases, software engineering, information systems, learning technology, HCI, CSCW, IT
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important that you are able to: demonstrate strong motivation, curiosity, and a learning-oriented mindset work independently, take initiative, and maintain good structure and discipline in their work
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. The supervision team includes: Prof. Ivan Depina – main supervisor and coordinator, probabilistic modelling, scientific machine learning Prof. Mohamed Hamdy – building performance simulation, building automation
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collaborative learning processes Developing the research competence required to complete a doctoral degree Required selection criteria You must have a professionally relevant educational background in psychology
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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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selection criteria Knowledge/experience with control engineering, information fusion and/or data assimilation, marine technology Knowledge of and hands-on experience with machine learning and/or statistical
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to achieve them. Acquire new knowledge quickly and use existing knowledge in new ways. Work constructively under pressure or in the face of adversity. Demonstrate strong problem-solving abilities with a