81 grounding-"https:"-"https:"-"https:"-"https:"-"https:" Postdoctoral positions in Netherlands
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- Delft University of Technology (TU Delft)
- Utrecht University
- Wageningen University & Research
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About the department The VUA Department of Computer Science has approximately 250 members, including 50 tenured staff members and 40-50 PhD students. The tenured staff members form the basis
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them to specific molecules and phenotypes. You will work here Wageningen UR has a global reputation for its ground-breaking research and innovative education in the fields of food and health, sustainable
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engineering, applied earth sciences, traffic and transport, water technology, and delta technology. Our research feeds into our educational programmes and covers societal challenges such as climate change
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mechanisms, approaches, and networks which will serve as the basis for a longer second phase (approval pending) which will build and expand this work. Through this postdoc, we aim to develop approaches
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of personal data in the context of the risk assessment is carried out on the legal basis of the GDPR: performing a public task in the public interest. You can find more information about this assessment on our
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of at least one academic reference We will review applications on a rolling basis and continue recruiting until the position is filled. A knowledge security check can be part of the selection procedure
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gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities
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certification of quantum states in realistic experiments. By combining experimentally grounded models with theoretical tools from quantum information, open quantum systems, and the foundations of quantum physics
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quantum and hybrid quantum-classical methods can make a real scientific difference, build reusable expertise and create the basis for future academic and public-private collaborations. At BDA, you will be
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designed for spatio-temporal data do not allow assessing the impact of interventions without capturing causal links. In this project, we aim to design algorithmic solutions grounded in causality