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
-
-of-year bonuses (8.3 %), training and career development. Our individual choices model gives you some freedom to assemble your own set of terms and conditions. Candidates from outside the Netherlands may be
-
into practice, so that end users can make better-informed decisions. For this purpose, PATH2ZERO aims to develop a digital twin. The main goal of this data-driven virtual representation of the inland waterway
-
the NWO project “PAving THe way towards Zero-Emission and RObust inland shipping (PATH2ZERO)”, which aims to develop breakthrough action perspectives and sustainable business models for all parties in
-
… 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
-
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
-
development, various types of leave, and options for sports and cultural activities. You can also tailor your employment conditions through our Terms of Employment Options Model. In this way, we encourage you
-
a postdoctoral researcher, you will: Integrate hybrid traffic models and data assimilation methods into a coherent prediction framework. Develop uncertainty quantification methods and explainable 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
-
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
-
-based Earth system simulations and predictability science: developing advanced data-driven methods to exploit the large amount and variety of EO data products to better reconstruct and simulate complex