Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
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
-
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
-
underground conditions. Apply machine learning and AI techniques to enhance model accuracy and optimize design parameters. Contribute to the development of a comprehensive, AI-based design methodology for LUS
-
fatigue. The research methods are based on both small-scale and full-scale experimental testing and on Finite Element Modelling. Timber structures have gained increasing attention in the European
-
3rd August 2025 Languages English English English The Department of Chemical Engineering has a vacancy for a PhD Candidate in process modelling, simulation and feasibility studies Apply for this job
-
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
-
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
-
modeling to simulate the pavement response under different loading conditions. The research will support improvements of the existing specification for the maximum authorized axle load and mass of vehicles
-
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
-
attachment. Main tasks Collect, compile, and analyze data to map the responses of plants and pollinators to climate change Participate in the development and adaptation of statistical models for analyzing