Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- DAAD
- Forschungszentrum Jülich
- ; The University of Manchester
- Cranfield University
- Vrije Universiteit Brussel
- ; Newcastle University
- ; University of Sheffield
- ; University of Southampton
- Aalborg University
- CWI
- Linköping University
- Monash University
- NTNU - Norwegian University of Science and Technology
- Nature Careers
- Newcastle University
- Prof. Ruilin Pei and Shenyang University of Technology
- University of Adelaide
- University of Copenhagen
- University of Nebraska–Lincoln
- University of Oslo
- Uppsala University
- Utrecht University
- Wageningen University and Research Center
- 13 more »
- « less
-
Field
-
the Novo Nordisk Foundation, that will drive research and innovations at multiple levels - from developing scalable quantum processor technologies to solutions for the quantum-classical control and readout
-
tuition fees. This PhD project in the area of autonomy, navigation and artificial intelligence, aims to advance the development of intelligent and resilient navigation systems for autonomous transport
-
and reproducible research, e.g., in the development of codes and algorithms. We will focus on devising computational solutions that can immediately be of use in other applications contexts as well
-
assessment, you will develop new, sample-efficient optimal control approaches for gate calibration and test them in numerical simulations. You will pursue your research with the German research collaboration
-
Your Job: develop numerical and analytical techniques to simulate and control the time dynamics of quantum technology devices implement and optimize gate operations and artificial Hamiltonians
-
Systems for hydrogen) studies the development of hydrogen systems from a socio-technical perspective. It considers both the economic and business cases of hydrogen systems, but also the system integration
-
oriented, regionally anchored top university as it focuses on the grand challenges of the 21st century. It develops innovative solutions for the world's most pressing issues. In research and academic
-
of structures, facilitating a form-finding process driven by FEM analysis. Training deep learning algorithms to suggest multiple structural concepts tailored to specific boundary conditions. Expanding FEM
-
powerful framework for decentralised machine learning. FL enables multiple entities to collaboratively train a global machine learning model without sharing their private data, thus enhancing privacy
-
skills and be interested in developing a collaborative program of applied research in robotics. For example, this may include sensor development, applied robotic perception, algorithm development, or other