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are seeking a motivated and enthusiastic colleague with strong computational skills in the analyses of complex data sets to join our teams. About the project We have generated advanced brain on chip models
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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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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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instrumented systems. You will conduct cost-effectiveness analyses by designing cost models to highlight trade-offs in the implementation of safety instrumented systems. You will evaluate how system design
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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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member's task is strongly intertwined with the tasks of the other team members. You will design, train and apply generative models that learn how to complete missing wedges in the reciprocal space of crystal
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models recapitulating aspects of neural-microglia interactions in neurodegenerative diseases at Ghent University. Lipid accumulation in microglia is a hallmark of neurodegenerative diseases such as
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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