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efficient navigation algorithms for multirotor operations around vessels. The role will focus on integrating drone airspace-usage predictions with Vessel Protected Volume models, developing optimisation and
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of Marine Technology at NTNU has a vacancy for a PhD Candidate in Deep Learning enhanced FSI modelling of Multi-modular Floating Structures. The position is part of the AIMOS project (Artificial Intelligence
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Espen Eidum 8th October 2026 Languages English English English Faculty of Engineering Sciences and Technology PhD Fellow in Distributed Acoustic Sensing for Arctic Railway Infrastructure Monitoring
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, interactomics, structural biology, and imaging datasets into predictive computational frameworks. Application of atomistic simulations, coarse-grained modeling, RNA folding prediction, RNA-protein and RNA-small
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heterogeneous digital health systems and for developing predictive models. D3. Controlling the financial costs associated with the use of agentic AI
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the synthesis of functional inorganic materials. You will be developing modelling methods to explain and predict how molecular additives can be used to control the formation of particular phases and produce
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developing simulation flows, analysis methodologies, and predictive models that enable Design-Technology and System-Technology Co-Optimization (DTCO/STCO) studies for future systems. You will work closely with
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rules for ceramic shell mould clusters; Experimental validation of the relationships between microstructure and thermal shock resistance; Development of multi-scale finite element models for predicting
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reliably assess fatigue damage and predict remaining lifetime, enabling proactive maintenance strategies that extend service life and reduce CO2 emissions. Through this PhD scholarship, you will contribute
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modelling skills to make a real-world clinical impact on early disease prediction and personalized medicine. Main duties and responsibilities The postholder will lead the numerical model development and