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model scenarios, and data which can be used to test the developed models. Measurements will include, for example, water content, and pressure head with local in-situ sensors. In addition we aim to carry
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Experience Appropriate PhD in a related field. Preferred Qualifications Experience with machine learning and deep neural network techniques. Experience with wearable and sensors placed in the environment
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subglacial hydrology. This NSF-funded project seeks to observe changes in subglacial hydrologic network geometry through two consecutive melt seasons by combining passive seismic, radar, and direct moulin
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technical excellence at the service of education, research, and innovation. As part of the project led by the SOTERN team in connection with the CREACHLABS grant—which aims to reconstruct, at the network
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protected and open field cultivation systems Use lab and field equipment (ICP, HPLC, gas exchange analyzer, soil/root/plant sensors, chlorophyll fluorescence, etc.), data loggers and image processing tools
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The opportunity The University of Liverpool is a key partner in a £14 million initiative (https://tinyurl.com/yc5z768m) to develop a sustainable, next-generation manufacturing facility, using
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redox balance. Our studies explore how p53 integrates metabolic cues by acting as both a sensor and regulator of cellular metabolism. In parallel, we are identifying metabolic changes that promote tumor
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network and the UPWELLING Academy. This academy will offer specialized training in emerging marine technologies and facilitate prototyping activities, empowering SMEs and startups while nurturing a new
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(Stockholm, Sweden) and the candidate will benefit from a strong (inter-)national network of collaborators in protease biology and computational proteomics. The successful candidate for this position will join
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the spatial reasoning capabilities of multi-mode large language models and hybrid AI systems combining artificial neural networks with symbolic AI. In-house research and development of one of these systems