Sort by
Refine Your Search
-
Listed
-
Employer
- University of Twente
- Delft University of Technology (TU Delft)
- Eindhoven University of Technology (TU/e)
- Maastricht University (UM)
- Wageningen University & Research
- Erasmus University Rotterdam
- University of Twente (UT)
- Erasmus MC (University Medical Center Rotterdam)
- KNAW
- NLR
- Radboud University
- RiboPro B.V.
- Tilburg University
- University Medical Centre Groningen (UMCG)
- University of Amsterdam (UvA)
- Utrecht University
- Vrije Universiteit Amsterdam (VU)
- 7 more »
- « less
-
Field
-
optimization methods for run-time network configuration and control. You will design efficient and lightweight learning-based techniques for automated scheduling, network resource allocation, and parameter
-
of performance, as they are very cautious by design. This, in turn, makes them less practical for problems where speed is of utmost priority. On the other hand, offline learning, such as Deep Learning, often
-
and decentralised data-center capabilities to optimize urban performance. This project aims to explore how telecommunications networks and urban infrastructures interdepend and co-evolve, and to
-
Knowledge of alternative propulsion systems (hydrogen, electric, hybrid) Familiarity with ATM concepts, airspace design, or traffic flow management Experience with optimization or operational research methods
-
optimization-based updates (e.g., stochastic gradient methods and Bayesian learning), Probabilistic performance guarantees, leveraging tools from stochastic systems, RKHS-based learning, and Bayesian inference
-
academic and industrial partners. Your colleagues: You will join the MERLN Institute and work within a multidisciplinary team spanning the IBE and CTR departments. Your colleagues include experts in
-
CHP units, the wider energy system risks losing a crucial flexibility resource. Through strategic integration hybrid energy storage systems with greenhouse operations via optimization methods, control
-
EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description We are looking for a PhD student who would like to optimize the use of real-world data (RWD
-
this project, you will investigate the optimal conditions and underlying mechanisms of Imagery Rescripting, a treatment aimed at alleviating distressing memories. You will begin by examining how
-
, patient motion, and more. Today, these parameters are either manually configured, heuristically optimized, or compensated post hoc using multi-level calibration scans or corrections, which introduces