Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Technical University of Denmark
- Aalborg University
- Nature Careers
- University of Southern Denmark
- Technical University Of Denmark
- Copenhagen Business School
- ; Technical University of Denmark
- ; University of Aarhus
- ; University of Copenhagen
- Aarhus University
- Geological Survey of Denmark and Greenland (GEUS)
- The University of Copenhagen
- University of Copenhagen
- 3 more »
- « less
-
Field
-
-learning based simulation models, can help research and business practice better understand international business activities OR (iii) the means by which machine learning techniques can be used
-
strong multi-disciplinary focus on energy markets, optimisation, game theory, control and machine learning. The EMA section (https://wind.dtu.dk/research/research-divisions/power-and-energy-systems
-
teaching courses and co-supervision of BSc and MSc. Qualifications MSc graduates with a background in either engineering, mathematics, computer science, computer engineering, physics, sustainable energy
-
Networks context. You are a committed individual with a strong background in engineering or applied mathematics / computer science, with a keen interest in scientific programming, machine learning and data
-
background in engineering, with a keen interest in scientific programming, machine learning and reliability engineering. Your curiosity drives you to explore and understand the intricacies of wind energy
-
experience within the field of optimization and machine learning You must also fulfill the requirements for admission to a PhD program at DTU. You must have a two-year master's degree (120 ECTS points) or a
-
science, machine learning and other methods. Within the section, you will be working within a diverse team of scientists at multiple levels of their career. Approval and Enrolment The scholarship
-
, the methods employed within the section include, system engineering, optimization methods, multi-disciplinary design optimization, uncertainty quantification, data science, machine learning and other methods
-
-Computer Interaction IT Governance, Architecture and Compliance Metaverse and Augmented/Virtual Reality (AR/VR) in Business Neuroscience and Digital Behavior Quantum Computing Robotics and Smart