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European sea basins over decadal timescales, due to coastal darkening (COD) and artificial light at night (ALAN), and will determine drivers, sources and impacts of these changes at both large and small
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team and lead the development and application of machine learning methods to large-scale genomic data generated at IPK-Gatersleben, with a focus on the impact of genetic variation on gene regulation
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countries. We also host a large data set of > 30,000 terrestrial insect species, based on DNA metabarcoding. Additionally, we have access to accompanying environmental data. These data sets provide a unique
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using geographic information systems (GIS) and programming languages (e.g. Matlab, Python, R) and working with large data sets and data formats, such as netCDF, HDF, including analysis tools such as NCO
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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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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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-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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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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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