Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- European Space Agency
- University of Groningen
- Wageningen University and Research Center
- Utrecht University
- Erasmus University Rotterdam
- University of Twente
- Leiden University
- Radboud University
- KNAW
- CWI
- Radix Trading LLC
- Universiteit van Amsterdam
- Nature Careers
- ; Maastricht University
- Qutech
- University of Amsterdam
- 6 more »
- « less
-
Field
-
your motivation letter. This project is part of the 10-year EMBRACER research programme funded by the Dutch Research Council (NWO). At EMBRACER, we work at the very frontiers of knowledge on climate
-
the DROPapp by integrating local and scientific knowledge. In this project, you will integrate the local forecasts based on observed local ecological indicators and scientific forecasts based on numerical
-
working memory contents held within. Second, we will use computational spiking-neuron models to explain the results of the experiments and implement the neural mechanisms responsible. These models will also
-
research is embedded in the institute’s research programme and you will be encouraged to develop interdisciplinary projects and acquire external research funding. Your key tasks are: Teach, improve and
-
are responsible for optimising REFM deliverables across sites by establishing a common set of strategic objectives, guidelines, performance and quality management systems, optimised methods and processes, planning
-
science, mathematics, physics, or a related field. You have affinity with numerical modelling, preferably atmospheric modelling or climate modelling, and mathematical theory of dynamical systems. You have
-
and processes) by shadowing as well as receiving coaching and tutoring from one of our Senior PA Engineers. You will perform this task in parallel to specific Mission Classification activities described
-
10-100 nm would be required, varying in absolute value over the surface of the wafer. An elegant method to correct wafer position is to include an adaptive element into the wafer stage, which allows
-
reduction initiatives, such as a transition to low-carbon energy supply, decarbonisation and the effective use of sustainable products and methods that address social impacts and improve returns; proposing
-
neurosymbolic AI to extract information from unstructured text. Use NLP methods for modelling narrative text. The focus on each of these tasks can vary based on the expertise of the applicant. The University