Sort by
Refine Your Search
-
Country
-
Employer
- UNIVERSIDAD POLITECNICA DE MADRID
- AALTO UNIVERSITY
- University of Groningen
- Academic Europe
- CNRS
- Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
- DAAD
- Forschungszentrum Jülich
- National Renewable Energy Laboratory NREL
- Universidad de Alicante
- University of Groningen; Groningen
- University of Newcastle
- VU Amsterdam
- WU Vienna University of Economics and Business
- 4 more »
- « less
-
Field
-
parametric design software. - Grades obtained in the subjects of architectural design, construction, and structures during undergraduate studies. - Experience in academic, research, and/or professional work in
-
mathematical methods, algorithms, and applications are required. Simulators are a recognized method for architectural design explorations and the implementation of software development platforms. The goal
-
and development in the field of software engineering for dependable and safe automated driving systems. Conception, design, and implementation of software architectures and prototypes in
-
mathematical methods, algorithms, and applications are required. Simulators are a recognized method for architectural design explorations and the implementation of software development platforms. The goal
-
Engineering). - Theoretical foundations of 6G RAN and autonomous systems o Proven knowledge of AI-native RAN systems. Indicative skills/experience: - Deep understanding of 5G/6G RAN architecture (O-RAN, NG-RAN
-
architectural design explorations and the implementation of software development platforms. The goal of this PhD is to create a modular and extensible simulation infrastructure that facilitates design
-
Reconfigurable/Spatial computing architectures, such as FPGAs, CGRAs, and AI accelerators, offer significant opportunities for improving performance and energy efficiency compared to traditional CPUs
-
applied Machine Learning Hands-on experience with High Performance Computing Systems Basic knowledge of System Architecture of Supercomputers and NVidia-GPUs Practical experience with ML/DL workflows and
-
comprise all aspects of applied mathematics, from model development and mathematical analysis to numerical implementation and statistical estimation of models as well as software packaging. What to expect
-
), técnicas y herramientas software de análisis de datos, machine/deep learning (Pandas, SHAP, TensorFlow, etc.) y específicas de análisis de imágenes, estadística, simulación, entornos cloud (tipo Kubernetes