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trustworthy medical AI? Deep models already outperform humans on many benchmarks, yet in the clinic they remain black boxes: radiologists cannot see why an algorithm flags a lesion, and AI engineers cannot tell
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%) doctoral scholarship holder or postdoctoral researcher in the field of circular value chain modelling and optimisation. Position You will work actively on the preparation and defence of a PhD thesis/Postdoc
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of teaching and research, the FSTM seeks to generate and disseminate knowledge and train new generations of responsible citizens in order to better understand, explain and advance society and environment we
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will be part of a team working overall on the implementation of 5D ED to solve and map the structures within multiphased particles during reactions and during changes in the environment. Each team
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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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datasets. Your focus will be on implementing and training generative models to decompose cylindrical projections. You will solve and refine the structures from the resulting decomposed data. You will map
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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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project dedicated to decoding early human embryo development through cutting-edge stem cell-based embryo models, single-cell omics, with a focus on X-chromosome inactivation and cell fate. The project
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will be part of a team working overall on the implementation of 5D ED to solve and map the structures within multiphased particles during reactions and during changes in the environment. Each team
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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