Sort by
Refine Your Search
-
Listed
-
Employer
- Technical University of Denmark
- Nature Careers
- Aarhus University
- University of Southern Denmark
- Aalborg University
- ; Technical University of Denmark
- Geological Survey of Denmark and Greenland (GEUS)
- University of Copenhagen
- ;
- ; University of Copenhagen
- Copenhagen Business School
- Roskilde University
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen
- 3 more »
- « less
-
Field
-
machine learning methods, including symbolic regression and neural networks. You will apply the algorithms to the discovery of new models in different fields, including robotic control, fluid mechanics and
-
guest metal ions and structural defects in metal oxides. The project focuses on understanding and utilizing redox properties of solid materials and the interactions between structural defects, metal
-
machine learning methods, including symbolic regression and neural networks. You will apply the algorithms to the discovery of new models in different fields, including robotic control, fluid mechanics and
-
driven optimization. The positions will consequently also focus on extraction of reduced order models using Gaussian Process modelling and/or Polynomial Chaos Expansion methods and deploying them in within
-
September 1st, 2025, or as soon as possible. The positions are for two years with potential for extension. We seek outstanding candidates to develop generative-AI-based statistical methods for blood-based
-
are defined: 1) Conceptual design principles and methods for resilient manufacturing systems. This topic will build upon existing theory on modular and reconfigurable manufacturing systems and develop methods
-
communication skills Following qualifications will be considered as an advantage: Experience with super-resolution techniques and physics-informed machine learning. Familiarity with explainable AI methods (e.g
-
contribute to teaching. Qualifications: You should have (or be close to achieving) a PhD degree. Background within computational methods for inverse problems, ideally tomography. Experience with development
-
). The successful candidate will contribute to the Nudge2Green research project, applying software development and AI methods to design digital nudging tools that promote sustainable consumer behavior in food choices
-
individual processes to entire manufacturing systems. The positions will all focus on factory and line level, where three research topics are defined: 1) Conceptual design principles and methods for resilient