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algorithms for microscopy image analysis problems (primarily 2D timelapse data), which are driven by real applications in life science research Developing solutions to integrate large foundation models
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RESPONSIBILITIES: Implementing laboratory and computational workflows for large-scale biological studies Collecting experimental and high-throughput data Characterisation of molecular and cellular mechanisms
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support and services for the analysis of large-scale omics data. RESPONSIBILITIES: Develop, implement, and maintain bioinformatics pipelines for various omics data, including RNASeq and scSeq besides others
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exchange, re-use of data, and data publication in clinical research according to the FAIR principles. RSPONSIBILITIES: Conduct research in an exciting, interdisciplinary large-scale project Analyze
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methods for the analysis of large-scale genomic, clinical, and phenotypic data, including phenome-wide association studies (PheWAS), statistical genetics, and precision medicine applications. This includes
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mechanisms and translate them into novel therapeutic strategies for neuroimmunologic diseases. The PhD Project involves: Planning and performing innovative large-scale experiments bridging human patient
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, (bio)informatics, and multimodal data analysis. The research group led by Dr. Johanna Raidt focuses on the identification of known and novel MMAF- and PCD gene variants using large patient cohorts
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of Experimental Medicine uses systems biological approaches incorporating a large variety of molecular data sets to gain a deeper understanding of the role of the microbiome in host health and disease and how it
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Intelligence) is being expanded into a leading German AI competence center for Big Data and Artificial Intelligence (AI). It is located at the University of Leipzig and the TUD Dresden University of Technology