Sort by
Refine Your Search
-
Category
-
Country
-
Program
-
Field
-
and development Our Exeter Academic initiative supporting high performing academics to achieve their potential and develop their career A multitude of staff benefits including sector leading benefits
-
clear anchoring in reality and benefit society as a whole. Ensuring gender balance at the Department of Electrical and Computer Engineering is a high priority at Aarhus University, and we particularly
-
an advanced PhD program. Our PhD students demonstrate high academic potential and deliver impressive results that benefit both the private and public sectors. Through our research and development activities, we
-
The Section for Electrical Energy Technology at the Department of Electrical and Computer Engineering (ECE), Aarhus University, is in a phase of rapid growth in both education and research
-
to allow high-capacity and high-quality operations and results. In particular, develop and validate a fully automated pipeline, enabling effective monitoring and treatment of methane emission records from
-
. The overall goal of the project is to design a novel high temperature heat pump. You will be conducting Computational Fluid Dynamic (CFD) simulations and cycle analysis, which will be instrumental
-
well-known for its skilled and very innovative interdisciplinary research environments with high international impact. We perform world-class research, which contributes with solutions to solve essential
-
collaboration between the Department of Electrical and Computer Engineering and the Novo Nordisk Foundation CO2 research center, Aarhus University, we aim to address this opportunity by developing digital twins
-
-known for its skilled and very innovative interdisciplinary research environments with high international impact. We perform world-class research, which contributes with solutions to solve essential
-
funding affect the subsequent performance of firms and scientists, in terms of outputs such as the number of papers, products, patents, etc. (Can an optimal applicant template be developed by training