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Field
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agriculture goes hand in hand with soil health and nature restoration, and a good revenue model for farmers. Between now and 2030, the ReGeNL project will help around 1000 farmers in the Netherlands transition
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scientific problems to help pave the way for a sustainable and healthy future. From forest fires to big data, from obesity to malnutrition, and from molecules to the moon: we cover the full spectrum
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(attention, memory, cognitive control), explores how brain and body rhythms interact to enable flexible cognition, and tests how rhythmic non-invasive neuromodulation can modulate cognition performances. We
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across diverse Dipteran species. Your duties and responsibilities include: Designing and conducting field experiments to record Dipteran swarming behaviour using 3D tracking systems Quantifying flight and
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-THEORETICALPARTICLEPHYSICS [#30493] Position Title: Position Type: Postdoctoral Position Location: Nijmegen, 6525 HP, Netherlands (Kingdom of the) [map ] Subject Area: Mathematics, Statistics, and Computer Science Appl
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candidate will be in the lead to develop organisational principles and action perspectives that help infrastructure agencies to collaboratively maintain our roads, bridges, waterways, electricity networks and
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to support safe-by-design development of plant-based meat alternatives improving supply chain sustainability and limiting food waste. The novelty of the project relies on the development of multi-species
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robotic systems and AI models. You will learn how to programme advanced robotic systems and how to implement aspects of deep learning and neural networks for chemical property prediction. You will be part
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changing spatial regulations. You will also help design economic decision-support tools to inform more inclusive and evidence-based marine policy. Your duties and responsibilities include: analyzing
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-modal prior information Job description The project is part of the IMAGINE open innovation lab (https://research.umcutrecht.nl/news/imagine-takes-off/ ), and aims to develop novel computational methods