Sort by
Refine Your Search
-
, the core scientific contribution of the SHARE project (Work Package 3). More concretely, your work will involve the following: You will design and compare deep generative approaches, UAEs, GANs, diffusion
-
, UAEs, GANs, diffusion models/flow matching, and Gaussian processes for realistic load, generation and voltage time series. You will embed physical constraints into generation: power-flow consistency
-
, UAEs, GANs, diffusion models/flow matching, and Gaussian processes for realistic load, generation and voltage time series. You will embed physical constraints into generation: power-flow consistency
-
, electric mobility, industrial electrification and modern power grids. New wide-bandgap semiconductor devices based on silicon carbide (SiC) and gallium nitride (GaN) can switch faster and reduce conversion
-
electrification and modern power grids. New wide-bandgap semiconductor devices based on silicon carbide (SiC) and gallium nitride (GaN) can switch faster and reduce conversion losses, but their performance is
-
activities open to everyone interested, fostering a welcoming and inclusive community. Your immediate Line Manager will be the Head of Department. About the project High-frequency wide-bandgap (SiC/GaN
-
analysis, such as MATLAB/Simulink, Python, finite-element tools or equivalent Essential Application/Interview Awareness/knowledge of field-oriented control, FPGA-based control, GaN inverter technologies
-
Vulnerability Detection of Smart Grids with a Specific Focus on Generative Adversarial Networks (GAN) Attacks Primary supervisors: Professor Damminda Alahakoon & Dr Shalinka Jayatilleke Other supervisors