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
-
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
-
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
-
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
-
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
-
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
-
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
-
biodiversity. Specifically, the primary focus of the PhD will be to analyse and parameterize models describing the ecological and evolutionary dynamics of small and fragmented populations, and how the risk of
-
Demonstrated knowledge and experience in electrical system modeling and analysis, applied control, power electronic conversion systems and/or optimization techniques. Experience and interest in experimental work