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Field
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stakeholders, including citizen scientists, environmental organisations, public administrations and policy makers Contribute to the further development and improvement of an existing digital knowledge platform
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, neuroinflammation, tau and α-synuclein pathobiology, digital pathology/AI image analysis, and mouse models of neurodegeneration. Education: A recent Ph.D. (less than 2 years of postdoctoral experience is strongly
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transcriptomics, methylation, proteomics, metabolomics, or digital pathology data. Experience with clinical trial datasets, electronic health record data, cancer registry data, or other real-world clinical datasets
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Postdoctoral Research Associate. The successful candidate will contribute to research projects focused on advancing automation, artificial intelligence, robotics, sensing, data analytics, and digital
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adaptation and participatory governance Manage project resources and contribute to the development of new funding opportunities Oversee the development of the citizen science platform and digital tools Assume
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, software applications, data pipelines, and digital platforms that support research, education, training, and community-focused initiatives Experience with programming languages, machine learning frameworks
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broad range of societal activities and as pioneers of tomorrow's digital society. As part of a tech university that aims to shape society, individuals and connections, our faculty works together
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Dencik and funded by an Advanced Grant from the European Research Council. The project explores the relationship between digital technology providers and European welfare states in the context of data
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genomics, multi-omics, and artificial intelligence to predict and prevent disease trajectories through precision medicines tailored to the right patient at the right time. Our vision is to create digital
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, software applications, data pipelines, and digital platforms that support research, education, training, and community-focused initiatives Experience with programming languages, machine learning frameworks