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emissions pathways (e.g., SSP-RCP scenarios), combined with observed runoff and flood data. Develop machine learning models to predict urban flooding and stormwater responses under climate change conditions
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dynamically over time. Second, clinical conditions such as infection, sepsis, ventilation, and hemodynamic instability are often interconnected, necessitating a holistic modeling approach. Third, there is a
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metocean and biogeochemistry models accounting for climate change impacts across Europe (from the Nordic Seas to the Black Sea and Mediterranean Sea) and the Pan-Arctic region. The PhD project focuses on new
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focuses on the modelling of liquid phase solvent degradation. The aim is to increase our understanding on how to design cost-effective CO2 capture plants and how process conditions impact degradation. Your
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combination with multi-fidelity response models. The multi-fidelity models may include combinations of physics-based response models, Artificial Intelligence (AI) models and probabilistic methods. Your
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31st July 2025 Languages English English English The Department of Civil and Environmental Engineering has a vacancy for a PhD Candidate in Hydrological and Water Resource Modelling in the Himalayan
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systems such as fuel cells and batteries. Intelligent control and management systems will be designed to enhance efficiency, sustainability, and seamless integration. Developed models and strategies will be
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metamorphic conditions, the exact mechanisms (dissolution–precipitation vs. dynamic recrystallization vs. mechanical transport vs. partial melting), the extent of mobility and role of fluids remain debated
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while keeping a comfortable temperature according to the user preferences. A smart system that utilizes next day electricity prices in combination with weather data and temperature data obtained from
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conditions. Implementing and calibrating material models (e.g., elasto-visco-plastic or elasto-plastic-damage models) using tools such as Abaqus, COMSOL, or ANSYS. Validating simulation results with