Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Employer
- Delft University of Technology (TU Delft)
- Eindhoven University of Technology (TU/e)
- CNRS
- Inria, the French national research institute for the digital sciences
- King's College London
- Linköping University
- NTNU - Norwegian University of Science and Technology
- University of Bergen
- University of Groningen
- Vrije Universiteit Brussel
-
Field
-
renewable energy use, energy security, and the reliable operation of hydro-dominated power systems. The project will focus on how AI can support advanced optimization models for hydropower and energy-system
-
part of a new lab at the Delft Center for Systems and Control, supervised by Gabriel de Albuquerque Gleizer. The research will allow you to gain deep insights across nonlinear dynamics, optimization, and
-
dissipative networks. We will view learning as a feedback interconnection of continuous-time (circuit) dynamics and an optimization algorithm. The key idea is to develop algorithms that minimise cost functions
-
Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 2 months ago
nonlinear optimal control algorithms. Experimentally validating the proposed methods on a waste-sorting robotic platform. Contributing to mechanical and mechatronic design choices whenever they influence
-
Are you fascinated by application-oriented research in mathematics and eager to work at the interface of numerical optimization, optical design, and uncertainty quantification? In this PhD project
-
nonlinear behavior makes it difficult to guarantee safety and stability. How can we exploit the expressive power of machine learning without compromising the rigorous guarantees required in safety-critical
-
. The objective will be to determine the optimal correction strategies as a function of tissue type and imaging depth. A second objective will be to exploit this platform for organ-scale mapping of intrinsic label
-
. The state-of-the-art approaches in optimal climate control of greenhouses are based on implementing economic objective functions exploiting a time scale decomposition between short-term climate control/energy
-
application! Your work assignments The project's contribution will lie at the intersection of random matrix theory and statistical inference theory, with applications in several fields of science. Special
-
, and computational techniques will be developed for automated optimization of snap fit geometry and performance. He/she will collaborate with the other PhD students and postdoc, involved in the project