PhD Position: Physics-Informed Generative AI for Synthetic Energy Data

EURAXESS hosting organisation · Multiple European countries

Can you help unlock the data needed for the energy transition? In the NWO-funded SHARE project, you will develop AI models that generate realistic, privacy-preserving synthetic energy data for grid planning and decision-making. Working with real-world data from Alliander, you will publish at leading machine learning venues while building tools with tangible impact on the Dutch energy sector. The Dutch energy transition depends on data that almost no one is allowed to see. Distribution system operators (DSOs), municipalities and energy communities need high-resolution grid and consumption data to plan grid reinforcements, heat networks and local flexibility, but privacy law (GDPR), commercial sensitivity and regulatory uncertainty keep this data locked away. Hence, critical infrastructure d

Funding and what it does not cover

Funding details were taken from the official programme page text. Confirm the current call before applying.