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Heritage and Education Economic and Spatial Development, Democratic Participation and Social Integration Biodiversity and Health Light, Matter, Information Environment and Sustainable Development Research
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different languages, to explore different transformational strategies for sustainable tourism. The specific tasks of this project would consist of document selection and review, data cleaning and pre
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-reconstructions and observations, low-order data assimilation, or deep neural networks. A quantification of the impact of mesoscale and submesocale features is also expected. At a later stage, the successful
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information at: http://www.ifw-dresden.de The Institute for Materials Chemistry (Director: Prof. Dr. Anjana Devi) at the IFW Dresden offers a PhD Position (m/f/d) on the following topic: Tailing and Exploring
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-sampling data. Furthermore, the position holder will play a central role in creating high-quality training datasets (seagrass maps) to support artificial intelligence (AI) algorithms used in related projects
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, business, and society. Our five core activities – research, nurturing young talent, policy advice, participation in public debate, and provision of information and service – are dedicated to sustaining and
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at both large and small scales. The scientific evidence-based knowledge developed in ISOLUME will be used to develop a roadmap for implementing changing marine lightscapes as an indicator in management
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, survey) or applied microeconometrics, and applied economics. You have experience with big data and machine learning methods? This would be a particular asset! With excellent English language skills, both
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motivated researchers with a MSc level knowledge in agricultural or hydrological sciences, with sound expertise in Remote sensing applications, big data integration, developing and applying deep learning
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different languages, to explore different transformational strategies for sustainable tourism. The specific tasks of this project would consist of document selection and review, data cleaning and pre