Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
: fluctuating renewable energy, dynamic electricity prices, and increasing system complexity. In the future, industrial energy systems will not simply run. They will understand themselves. They will learn from
-
-fidelity numerical models to be analysed under regular and irregular sea states (e.g., coupled hydrodynamic–structural models and/or FEM workflows). Develop surrogate models representing the coupled dynamic
-
Learning models to understand and predict interactions in dynamic ecological networks. Our lab is looking for candidates for the following stipend: Learning the Structure and Dynamics of Complex Networks We
-
, engineers and more working together to fulfil the mission of the programme. We offer creative and stimulating working conditions in dynamic and international research environment. The group is a part of the
-
. The duration of the position is three years. Your work tasks In this PhD position, you will work with the spatial and temporal dynamics of shallow groundwater in urban areas. The overall aim is to obtain a
-
into the model. Finally, the satellite-fed VIC model will be run for short-to-seasonal predictions of water dynamics for various dryness scenarios. Profile The ideal candidate has: MSc degree in Geodesy, Hydrology
-
, cluster structures, flat surfaces, and spectral networks. The goal of the project is to build new far-reaching connections between algebraic geometry, dynamical systems, and mathematical physics using a
-
stimulating working conditions in a dynamic and international research environment. Our research facilities include modern laboratories and a number of core facilities (animal unit, flow cytometry, in vivo
-
, bonding technologies, and multi-layer stack-up integration for glass-based PCB structures. Multi-physics simulation and experimental characterization will be used to analyze thermo-mechanical behaviour
-
. The pace is uneven across countries. Regulatory frameworks, labour markets, platform structures, and the resources firms can actually draw on (access to model providers, sector-specific data, firm size, and