Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
a team of 25 colleagues dealing with CCUS, and industrial partners in Denmark as well as abroad. Your primary tasks will be to: Apply AI in context of capture solvent modelling Understand and analyse
-
mathematical foundation of machine learning models. You will be responsible for developing scientific machine learning methodologies enabling new approaches for solving machine learning problems including
-
at the Niels Bohr Institute, Faculty of Science, University of Copenhagen. We are located in Copenhagen. We offer creative and stimulating working conditions in a dynamic and international research environment
-
competences within computational modelling, optimization and integration of thermal energy storage technologies – such as large water pits and phase change material storage. You will work with colleagues, and
-
with researchers at DTU and KTH, you will help develop an integrated decision-support system that: Uses real-time sensor data and AI models to assess risk scenarios. Dynamically recommends optimal
-
collaboration that covers all aspects of our research: theory and modeling, sample growth and fabrication, experiments and demonstrations. We have created a dynamic research environment of young and senior
-
within the broad topics of modelling tool-workpiece interaction in mechanical material removal processes, zero-defect manufacturing, machining system performance characterization as well as on-machine and
-
both technical insight into data modeling and a solid understanding of how real-world engineering data is generated, structured, and used. We are seeking motivated candidates with strong programming
-
), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics. Our research is rooted in basic research and centres on mathematical models of the physical and virtual
-
PhD scholarship in Runtime Multimodal Multiplayer Virtual Learning Environment (VLE) - DTU Construct
planning and scheduling. In the furthermore, core works are envisioned in (c) initiating novel VLE design using foundational Digital Twin for Construction Safey (DTCS) components (e.g., city models, nD BIM