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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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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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dementia; mild stages of Long-COVID). Prof. Synofzik coordinates multiple large trans-European consortia on translational trial-readiness research and participates in Long-COVID research. He leads several
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the world. We are seeking a highly motivated Postdoctoral Researcher with expertise in large-scale omics data analysis to establish an innovative multi-omics data integration workflow. This unique position
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close collaboration with international and national partners You will analyze and integrate various types of generated data (e.g., next-generation sequencing, large-scale genomic, transcriptomic
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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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. Central to its objectives is the development of methods for culturing tailor-made organoids, assembloids and co-organoids for inter-organ communication towards AI-supported large-scale / high-throughput
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. Central to its objectives is the development of methods for culturing tailor-made organoids, assembloids and co-organoids for inter-organ communication towards AI-supported large-scale / high-throughput
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us We are TUM’s unique Pathology AI lab developing new machine learning (ML) methods for automatically analyzing digital pathology data and related medical data. Such methods include the automatic
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. The position is part of the project “Understanding of, and Explanations with, Large Language Models”, which is funded by the Volkswagen Stiftung and associated with the Cluster of Excellence “Machine Learning