Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Employer
- NEW YORK UNIVERSITY ABU DHABI
- The University of Alabama
- Bowdoin College
- CNRS
- Delft University of Technology (TU Delft)
- University of Utah
- AALTO UNIVERSITY
- Aalto University
- Centar izvrsnosti MARBLE drustvo s ogranicenom odgovornoscu za istrazivanje i razvoj
- KU LEUVEN
- Nanyang Technological University
- Universidad de Sevilla
- University of California, Berkeley
- University of Copenhagen
- University of Michigan
- University of Pennsylvania
- University of Sheffield
- University of Washington
- Wageningen University & Research
- 9 more »
- « less
-
Field
-
accepted all year round Details Dynamic optimization is integral to many aspects of science and engineering, commonly found in trajectory optimization, optimal control (e.g. model predictive control
-
, hydrodynamic, energetic, and control models of the platform. This digital twin will be used for performance prediction, system optimization, control development, and mission and trajectory planning while
-
; autonomous decision-making; robot localization and navigation. Experience in one or more of the following: path planning, motion planning, trajectory optimization or model predictive control; reinforcement
-
successful candidates will develop fundamental theory and practical algorithms that move reinforcement learning closer to real-world systems. Position 1 will focus on trajectory-centric optimization
-
theory and practical algorithms that move reinforcement learning closer to real-world systems. Position 1 will focus on trajectory-centric optimization, Position 2 on adaptive policies, and both will
-
maneuvering, ensuring both precision and reliability in collision avoidance. 3 METHODOLOGY Low-thrust trajectory optimization relies on continuous, long-duration thrusting, typically implemented using
-
Centar izvrsnosti MARBLE drustvo s ogranicenom odgovornoscu za istrazivanje i razvoj | Croatia | about 2 months ago
optimization-based mission planning, task allocation, trajectory coordination, and control algorithms for heterogeneous multi-robot systems Integrate developed methods with robotic platforms and contribute to
-
data assimilation, optimization, Bayesian inference, inverse modeling, or related quantitative methods. Experience with atmospheric transport, dispersion, trajectory, or source-receptor modeling
-
Delft University of Technology (TU Delft) | Delft, Provincie Zuid-Holland | Netherlands | 29 days ago
complex systems, from sustainable energy grids to autonomous mobility. In this ERC-funded PhD project, you develop cutting-edge game-theoretic control and optimization methods. Job description Modern
-
quality and safety associated with reducing the intensity of CIP processes making optimization challenging. Monitoring tools and advanced data analytics at industrial scale provide an opportunity that