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partners to reduce CO2 emissions in steel production using machine learning. You can find more information here . You will work on a theoretical and an applied project on data-enhanced physical reduced order
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. This is an innovative nature-inclusive approach to develop future-proof, sustainable methods to produce healthier and higher quality seafood, and to improve seafood security, human health, and the
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records from satellite data, and/or improved methods of uncertainty characterisation, including the use of artificial intelligence and machine learning to improve or analyse satellite climate data records
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-organise a theme day during a summer school (scheduled in 2027) on the role of dike grassland management in water safety and biodiversity. Lastly, you will co-design and teach an educational module on dike
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Applications are invited for a Postdoc position within the research project “Uncovering the creative process: from Inception to Reception of translated content using machine translation” (INCREC
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fish detection technologies to support fish monitoring and more selective and sustainable flatfish fishing. This Postdoc project is supported by the Ministry of Agriculture, Fisheries, Food Safety and
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supported by the Ministry of Agriculture, Fisheries, Food Safety and Nature of the Netherlands, Wageningen University, and Wageningen Marine Research. It aims to develop: (1) a validated prototype of an
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, and you are expected to develop showcases for this new platform, and develop ideas to implement in a business. For this you will learn and exchange ideas within the Biotech Booster community
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, aiming to transform the care for patients with abdominal aortic aneurysms (AAA). You will develop and validate cutting-edge multimodal deep learning models that integrate imaging and clinical data
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assessment. You will be provided with access to various engineering and computation toolsets along with the high-performance computer. A good background in numerical methods and computational platforms is