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candidates to conduct research in the field of evidence synthesis. The projects will focus on the development of statistical methods for the synthesis of complex data. About the research group The new research
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researchers. The centre is internationally recognized, with interests spanning a broad range of research areas in biostatistics, machine learning and epidemiology and numerous collaborations with leading bio
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of the position. The successful candidate will have a solid theoretical foundation in one or more of the topics: Computational Mechanics, Finite Element Analysis (FEA), Numerical Optimization
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spanning a broad range of research areas in biostatistics, machine learning and epidemiology and numerous collaborations with leading bio-medical research groups internationally and in Norway. OCBE is a
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, or geometric deep learning. Experience with optimization methods, numerical modeling, or simulation of complex systems. Experience with 3D modeling, CAD APIs, or computational geometry is an advantage
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with optimization methods, numerical modeling, or simulation of complex systems. Experience with 3D modeling, CAD APIs, or computational geometry is an advantage. Experience and abilities
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, and the costs of the inspection and maintenance processes. The research will target a novel data-driven and holistic approach using probabilistic AI methods and optimization-based decision making
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systems. By combining microclimate modelling, remote sensing data, and data-driven methods, the results are integrated into a Digital Twin framework. The research will support predictive risk assessment and
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methods and optimization-based decision making. Are you motivated to take a step towards a doctorate and open exciting career opportunities? As a PhD Candidate with us, you will work to achieve your
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plan proposal for academic supervisor(s) The project description must describe the topic, research question, theoretical basis, and choice of method. In addition, you must provide information about your