Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
thereafter. You will join the Section for Electric Power Systems and Microgrids at the Department of Energy and contribute to developing future integrated energy systems that support the green transition. Your
-
applications for a PhD position within the project “HVDC Subsea Electrode Unit”, starting from May 2026 or soon hereafter. The 3-year employment is funded by the Energy Technology Development and Demonstration
-
through online surveys and interviews, prototype development for accessible setup and operation of nanoservers (both on web and mobile platforms), and longitudinal evaluation of the prototypes through live
-
is funded by the Energy Technology Development and Demonstration Programme (EUDP) and aims to deliver a standardised, robust, and scalable subsea electrode unit for HVDC systems. The successful
-
planning, allowing them to function as a coordinated unit. The multi-vehicle platform will be developed by the project partners throughout the project and validated in offshore conditions. PhD Focus Area
-
School, where collaboration, analytic depth, and strong academic ambitions shape our work. We are looking for scholars who wish to contribute to developing research and teaching in strategy and management
-
. As a Postdoctoral Researcher in AI-Driven Grid Flexibility Coordination and Energy Storage Integration, your main tasks will include: • Develop AI-driven control strategies for grid-forming
-
to technically oriented candidates with expertise in AI and interactive systems development. Scientific dissemination is expected to focus on leading Human-Computer Interaction venues. For further information
-
return migration as well as later-life social and political integration among older non-Western immigrants in Denmark. The work consists of quantitative research, including developing research questions
-
digital twins be used to provide on-line predictions as to the future expected evolution of these critical properties as the basis for safe reinforcement learning (RL) for on-line optimal control”. In