Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Cranfield University
- Technical University of Munich
- ;
- Technical University of Denmark
- Nature Careers
- Forschungszentrum Jülich
- Fraunhofer-Gesellschaft
- Ghent University
- Monash University
- University of Groningen
- Chalmers University of Technology
- Curtin University
- University of Southern Denmark
- ; The University of Manchester
- NTNU - Norwegian University of Science and Technology
- Umeå University
- University of Adelaide
- University of Twente
- Vrije Universiteit Brussel
- ; Swansea University
- DAAD
- Radboud University
- SciLifeLab
- ; Newcastle University
- ; Technical University of Denmark
- ; University of Cambridge
- ; University of Leeds
- Aalborg University
- Erasmus University Rotterdam
- Linköping University
- University of Cambridge
- University of Copenhagen
- University of Nottingham
- University of Southern Queensland
- ; Aston University
- ; Brunel University London
- ; University of Birmingham
- ; University of Bristol
- ; University of East Anglia
- ; University of Exeter
- ; University of Oxford
- ; University of Sheffield
- ; University of Southampton
- ; University of Surrey
- ; University of Warwick
- Aarhus University
- Blekinge Institute of Technology
- Copenhagen Business School , CBS
- Deutsches Elektronen-Synchrotron DESY •
- Harper Adams University
- Helmholtz-Zentrum Geesthacht
- Institut Pasteur
- Leibniz
- Leiden University
- Lulea University of Technology
- Max Planck Institute for Molecular Genetics •
- Max Planck Institutes
- Queensland University of Technology
- Trinity College Dublin
- University of Antwerp
- University of Bern
- University of Bremen •
- University of Oslo
- University of Potsdam •
- Uppsala University
- Utrecht University
- Wageningen University and Research Center
- 57 more »
- « less
-
Field
-
information from high-quality videos that share content with distorted footage as constraints in the learning process of modelling algorithms. This method uses the characteristics and knowledge embedded in high
-
on building the next generation of quantum processors based on superconducting circuits. To achieve this ambitiuous goal, we have a variety of projects related to: Development and optimization of nano
-
vehicles capture videos or images for underwater pipes for inspection purposes. However, highly blurry or poor-quality videos can only be received under noisy environment. Therefore, developing accurate
-
structure, and of the force and tidal field that has been shaping the cosmic web. The basic detection algorithms to infer the overall structure of the cosmic web are the various versions of the scale-space
-
supply and a path to a net-zero-emissions society. SecurEL aims to develop new knowledge addressing research challenges arising from accelerated electrification and increased use of the existing grid
-
industrial partners and is partly externally funded by the KK Foundation. In co-production with our corporate partners and the community, we develop concepts, principles, methods, algorithms, and tools
-
-rounded academic background ◾Demonstrated ability to develop precision mechatronics system and algorithms ◾Ability to develop kinematic and/or dynamic analysis of mechanical/robotic systems ◾Ability
-
the development of new algorithms for processing, analysis and inversion of active and passive seismic data and the application of these algorithms to field data. Student type Future Students Faculties and centres
-
education . Skills and personal qualities In addition to the aforementioned requirements for the position: A demonstrable computational competence, comfortable with using and developing algorithms, data
-
processing, algorithm design, optimisation and simulation, software engineering and automation and control systems. An overview of the current PhD research projects is given here: https://www.dashh.org