36 machine-learning-"https:"-"https:"-"https:"-"https:"-"Ulster-University" positions at Aarhus University in Denmark
Sort by
Refine Your Search
-
description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will
-
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
-
the Department of Electrical and Computer Engineering, please visit https://ece.au.dk/ . Visit our LinkedIn: https://www.linkedin.com/company/au-ece/ Research areas in the department Electrical and
-
analysis to translate THz signals into optical material properties such as refractive index and absorption coefficient. Development of machine learning algorithms for material classification. Exploration
-
Research Focus We are offering a Postdoctoral position in graph machine learning, algorithms, and graph management with particular focus on: Modeling real-world spatio-temporal energy networks Developing
-
-constrained machine-learning (ML) models in simulations of turbulent flows. You are expected to contribute to research and development in data-driven methodologies for turbulence modeling in LES (i.e., wall and
-
biogeochemical modelling and data-driven machine learning approaches at an ecosystem scale to improve our understanding of the fate of nitrogen fertilizers applied to agricultural soils. This understanding will be
-
intelligent control and aerial robotics for navigation in uncertain environment. You will be mainly responsible for implementation of machine-learning algorithms for unmanned aerial vehicles; validation
-
with troubleshooting their machines and support their understanding of core concepts. Guide students in working on their own project. Demonstrate best practices and foster the development
-
identification, and who have significant experience in applying Machine Learning (ML) and Artificial Intelligence (AI) to these areas. Applicants with theoretical, numerical, experimental, or combined research