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                (EKFZ: https://ekfz.uni-goettingen.de) Your tasks Large-scale and in-depth characterization of optimized Channelrhodopsin variants for basic research in neuroscience and future optogenetic therapies 
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                analyzing data from large cohorts, ideally within the NAKO German National Cohort Experience in teaching epidemiology to students Desirable qualifications Experience in the field of metabolic diseases 
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                data mining. The group provides a strong network to local AI expertise (e. g. Hessian.AI, TU Darmstadt), large scale compute infrastructure, as well as a broad international network (Stanford, UC San 
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                the integration of large-scale biological datasets derived from both the host and the microbiome, employing advanced statistical methods and cutting-edge artificial intelligence techniques to uncover novel insights 
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                Large-scale and in-depth characterization of optimized Channelrhodopsin variants for basic research in neuroscience and future optogenetic therapies Automated (Syncropatch384, Nanion) and manual patch 
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                tasks You will carry out research tasks in Prof. Wende's working group, particularly in the field of element-specific investigation of functional magnetic materials at large research facilities. In 
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                of Freiburg, founded in 1457, belongs to the best universities of Germany. Freiburg has a large international studen body and is located in the Black Forrest with a 30-minute drive to both Switzerland and 
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                , including but not limited to cancer, metabolic disorders, and infections. The research design involves the integration of large-scale biological datasets derived from both the host and the microbiome 
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                want to contribute to tackling one of the big challenges of our time – then you may want to apply to the position in our team, which is expected to start on 01.11.2025. Appointment is conditional 
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                or related with strong bioinformatics background) (m/f/d) with focus on the analysis of cutting-edge liquid biopsy proteomics, transcriptomics and other omics data sets related to blinding diseases, such as