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30th March 2026 Languages English English English The Department of Structural Engineering has a vacancy for Two PhD positions in “Micromechanics-based modelling of ductile failure in high-strength
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particle clustering and morphology affect strain localization and damage evolution. Integrate experiments and modelling to create predictive tools for recycled alloy performance. Your immediate leader is
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the Telemark Canal , focusing on digital twin-based preparedness modelling for cultural heritage infrastructure. The primary objective of the position is to complete a doctoral education leading to a PhD degree
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, as well as from industry. The successful candidate will work in the established collaboration between DSB and ICGI to develop multimodal deep learning models for predicting prostate cancer
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quantification, in particular the theory and methods known as predictive Bayes. Predictive Bayes theory involves getting Bayesian type uncertainty for parameters given data (i.e., a posterior type distribution
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particle clustering and morphology affect strain localization and damage evolution. Integrate experiments and modelling to create predictive tools for recycled alloy performance. Your immediate leader is
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selection criteria You must have strong competence in artificial intelligence, signal processing, modelling, instrumentation, or control, including good programming skills. This background is typically
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interactions. This involves (i) developing predictive machine learning models that forecast user actions and remote system responses across audio, video and haptic modalities, and (ii) jointly orchestrating
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SFI FAST: PhD position in Microstructure/texture evolution during extrusion of scrap-based Aluminium
microstructure evolution during extrusion is critical for controlling final mechanical properties and surface appearance of extruded profiles, yet quantitative predictions remain challenging due to the complexity
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the University of Oslo. Place of work is the Department of Mathematics at Blindern, Oslo. Ocean waves follow complex patterns influenced by wind, currents, and the shape of the seafloor. Predicting