Sort by
Refine Your Search
- 
                Listed
- 
                Category
- 
                Employer- Technical University of Denmark
- DTU Electro
- Nature Careers
- Technical University Of Denmark
- University of Southern Denmark
- Aalborg University
- Danmarks Tekniske Universitet
- Technical University of Denmark;
- Aalborg Universitet
- Aarhus University
- Technical University of Denmark (DTU)
- Technical University of Denmark - DTU
- University of Copenhagen
- 3 more »
- « less
 
- 
                Field
- 
                
                
                : Microphone array processing. Acoustic measurements. Statistics and machine learning. Optimization and inverse problems. Excellent communication skills. Your primary responsibilities will be: Conduct original 
- 
                
                
                , optimization, deep learning, or information theory; Experience in programming, e.g., in C++, Python or Matlab. Qualification requirements PhD stipends are allocated to individuals who hold a Master's degree. PhD 
- 
                
                
                inactivation. Designing and optimizing multi-step and systems biocatalysis workflows, including flow chemistry and cascade reactions. Developing and applying modeling tools to evaluate kinetics, enzyme stability 
- 
                
                
                , optimization, control, game theory, and machine learning. Interdisciplinary by design: Work at the intersection of energy systems and markets, privacy and cybersecurity, forecasting, optimization, control, game 
- 
                
                
                -enhanced exact methods, particularly focusing on Column Generation (and Branch-and-Price), to improve scalability and convergence in solving complex optimization problems. In collaboration with your 
- 
                
                
                technology, positioning your career for long-term success and global scientific impact. Your primary role will be to pioneer and optimize advanced electron-beam lithography techniques to demonstrate reliable 
- 
                
                
                batteries (RFB), enabling affordable and durable long-duration energy storage. The approach is to use hierarchical structures, i.e., complex material layers that can be optimized to specific battery 
- 
                
                
                , have been optimized for fossil fuels for more than 140 years but the new fuels have properties that can enable a more efficient operation. Advanced combustion processes like HCCI, SACI and PPC will be 
- 
                
                
                challenges. This PhD project aims to advance the efficient, controllable, and optimized use of renewable energy by integration of advanced TES technologies (latent heat and thermochemical storage) in 
- 
                
                
                analytical skills, including signal processing, statistical learning, optimization, deep learning, or information theory; Experience in programming, e.g., in C++, Python or Matlab. Qualification requirements