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analysis in R and with multi-level modeling WHAT WE CAN OFFER YOU We offer you a temporary appointment for a period of 2 years. The appointment cannot be renewed Even if you have already been appointed
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Intelligence. You have a demonstrable interest in research into the use of Large Language Models to support GDPR-compliant Requirements Engineering. You have experience in supervising students in academic and/or
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integration, network biology and/or modelling of protein interactions, preferably with a focus on the development of computational methods and/or AI-based methods) Good programming skills and mathematical
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trials (e.g., diet, FMT), and ex vivo gut models enabling advanced multi-omics analyses of these samples. In addition the lab also maintains a large culture collection, partially linked to genomic data
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intervention trials (e.g., diet, FMT), and ex vivo gut models enabling advanced multi-omics analyses of these samples. In addition the lab also maintains a large culture collection, partially linked to genomic
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electrophysiology to translational models, including animal studies and analyses of human tissue samples. This full-stack methodology enables us to directly link molecular channel function with disease phenotypes
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critical roles of ion channels—particularly the TRP superfamily—in physiological and pathological processes. Our interdisciplinary approach spans from foundational electrophysiology to translational models
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academia and practice regarding the cost-effectiveness analysis of safety instrumented systems. You will conduct cost-effectiveness analyses by designing cost models to highlight trade-offs in
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the field of analytical and/or simulation methods for composite materials. You have extensive experience with development and implementation of algorithms for modelling of composites You have experience with
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-scale screens to study fundamental principles in molecular and complex trait genetics using microbes as model systems. Our core technology MAGESTIC (https://doi.org/10.1038/nbt.4137 ), a CRISPR/Cas9-based