211 machine-learning "https:" "https:" "https:" "https:" "https:" "University of St" "St" Postdoctoral positions in Denmark
Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
is a successful academic community that strives to put knowledge into action by: Engaging partners in the co-creation of knowledge, learning and social change. Empowering our students to become
-
. Software or code development, incl. artificial intelligence and machine learning. Automation and robotics, incl. safe human-machine interaction. Serious gaming, incl. AR/VR. Life cycle analysis. You are
-
imaging, deep proteomics, metabolomics, metaproteomics, and machine learning (ML) approaches to develop diagnostic classifiers, spatial tissue atlases, and identify potential therapeutic targets
-
Committee. You can read about the recruitment process at https://employment.ku.dk/faculty/recruitment-process/ . Interviews will be held on 27 April 2026.
-
: • Develop AI-driven control strategies for grid-forming inverters to enhance grid flexibility, reliability and stability. • Apply machine learning and AI tools for the battery system health estimation
-
and maintenance of monitoring buoys and related sensor systems. Apply image analysis and machine learning techniques to ecological datasets. Develop and implement multi-platform monitoring frameworks
-
10 research sections. We broadly cover digital technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning
-
an opportunity to actively engage as a collaborative partner in different projects depending on their interests and expertise. Learn more about the Center and our research, vision, and values here . About the
-
, that can be documented by a publication record in relevant venues. Solid understanding of state-of-the-art embedded machine learning techniques. Experience in system-level programming, developing prototype
-
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