Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
-
Optimal Transport for Optimization and Machine Learning Appl Deadline: 2026/02/04 11:59PM (posted 2025/12/19, listed until 2026/02/04) Position Description: Apply Position Description Doctoral student in
-
dimensionality reduction * development of optimization algorithms and numerical modeling procedures * development of simulation models using commercial packages (CST, ADS, HFSS, etc.) * writing technical reports
-
is actively involved in numerous projects. Candidates are expected to demonstrate a strong track record in developing and applying advanced computational methods to optimize the performance
-
in at least one of the following: optimization, PDEs, optimal control, numerical analysis/scientific computing, or machine learning for differential equations and control. Evidence of research
-
-armed Bandits, Bayesian Optimization. Automated Model Design and Tuning: Neural Architecture Search, Hyperparameter Optimization. Computer Networking: Resource-Constrained Networking (e.g., Internet
-
, optimization and associated numerical methods is considered a bonus. As a PhD researcher of the KU Leuven LMSD division and TUE Mechanics of Materials group perform research in a structured and scientifically
-
numerical analyses and material characterization), laboratory testing and data analysis towards validation and upscaling, as well as system-level investigations towards commercialization. The latter
-
the ability to manage numerous tasks and deadlines. Key Responsibilities Serve as the primary point of contact for all CRM-related activities, including configuration, customization, and optimization
-
List relevant coursework and lab experience as well as all papers, presentations, or publications you may have authored or co-authored. Include any reprints or abstracts if they are available. Three
-
, mathematical finance, or optimization and is capable of actively contributing to research projects in these fields. The contract start date is flexible, beginning as early as March 1, 2026. The employment