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Field
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sensor data, and (iii) sophisticated fatigue analysis models combining advanced fracture mechanics with crack initiation and growth simulation. Additionally, you will explore fatigue mitigation strategies
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to new developments. The candidate will join the System Software Group , and study the performance and scalability characteristics of adapting scientific simulation software to current and future
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modeling, computer simulation, non-linear model analysis, interactive learning environments and decision-laboratory experiments. About the project/work tasks: Description of the INTEGRATOR project
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communications. The project includes training in AI, cyber security, FL, privacy-preserving computation, edge intelligence, and UAV simulation. Objectives Define a UAV-PFL threat model covering poisoning, backdoor
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will be employed and tested on actual measurement data as a benchmark. The project will involve mathematical modeling, construction of numerical methods, coding, testing, numerical simulations, and
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, including satellite-derived soil moisture and environmental observations, in-situ measurements and land-surface model simulations. Data assimilation and related multi-source data integration techniques will
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to investigate cascading cyber effects, cyber resilience, and advanced cyber range modelling. The research combines simulation, software development, and experimental validation in the Norwegian Cyber Range
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simulated driving tasks.The PhD candidate will contribute to experimental design and protocol implementation.They will participate in participant recruitment and the acquisition of behavioral, EEG and eye
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scientific knowledge, such as physical laws, differential equations, and domain-specific constraints, to model, simulate, and understand complex systems. The project will explore modern SciML methods
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Prof. Igor Zozoulenko). Our focus is on: Machine-learning accelerated materials simulations ML-accelerated simulation of ion and charge carrier transport in energy materials Multiscale modeling