Sort by
Refine Your Search
-
Listed
-
Employer
- Delft University of Technology (TU Delft)
- Utrecht University
- European Space Agency
- Eindhoven University of Technology (TU/e)
- Leiden University
- Maastricht University (UM)
- University of Twente (UT)
- University of Utrecht
- Wageningen University & Research
- ARCNL
- Erasmus University Rotterdam
- Radboud University Medical Center (Radboudumc)
- SRON
- Universiteit Leiden
- University of Amsterdam (UvA)
- University of Twente
- 6 more »
- « less
-
Field
-
Infrastructure? No Offer Description Use real-world vessel data, agent-based modelling and digital twin technology to accelerate the transition toward zero-emission inland shipping. Job description The
-
Use real-world vessel data, agent-based modelling and digital twin technology to accelerate the transition toward zero-emission inland shipping. Job description The postdoctoral research is part of
-
… Requirements Specific Requirements We seek candidates who are motivated about eMRV research, can lead field campaigns, and are self-driven and can work independently and with a team. Applicants should hold a PhD
-
explore circuit architectures such as local digitisation, event-driven or asynchronous readout, and noise-immune topologies to achieve robust, ultra-low-latency tactile sensing with a high dynamic range
-
estimation using data-driven dithering Subspace and DOA estimation under coarse quantization Preprint versions can be found on Arxiv. These works are representative for the type of mathematics involved
-
development. Job requirements We are looking for a highly motivated and independent postdoctoral researcher with a strong interest in multiscale modelling. The candidate should meet the following requirements
-
traffic flow theory with machine learning, and with that, the best of both worlds: theory and logic where necessary, data-driven where possible. This innovative new approach enables more efficient and
-
to develop a new generation of traffic prediction methods, combining traffic flow theory with machine learning, and with that, the best of both worlds: theory and logic where necessary, data-driven where
-
be involved in the scientific activities of the Science Section within at least one of the following thematic priorities (please indicate your preferred theme in your proposal). Data-driven and AI
-
and applications of Remote Sensing, who is also enthusiastic about incorporating AI-based and data-driven methods to extract new insights from Earth Observation data. We are particularly interested in