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are seeking a postdoctoral researcher with experience in analysis of large datasets to examine pre- and post-diagnosis healthcare utilisation among patients with cancer in Luxembourg using insurance claims data
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historians, data scientists, and digital humanists Publish in peer-reviewed journals and present at international conferences Assist in the coordination of D4H activities, including seminars, symposia, and
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Post-doctoral Researcher in Multimodal Foundation Models for Brain Cancer & Neuro-degenerative Disea
response to therapies, with applications in brain tumours and neuro-degenerative diseases. Our data comes from large public cohorts as well as local proprietary databases of clinical and preclinical medical
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-read whole-genome sequencing data. Genome of Europe will operate in a federated analysis paradigm, with raw-datasets being held separately in different member states, hence the central opportunity
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. The Postdoctoral researcher will conduct methodologically innovative, data-driven research in field of Migration in Contemporary History of Luxembourg and the Greater Region and actively contribute to historical
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institutes and organisations. Your responsibilities: Conduct practice-oriented research using qualitative data collection and analysis methods (e.g. qualitative interviews with young people) Design, implement
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multi-modal models, contributing to bridge transport economics, network modelling and activity-based modelling, and leverage different types of (big) data. The applicant should be a creative and motivated
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of the Research Group "Contemporary History of Luxembourg" For further information about this position, please contact Christoph Brüll: Your profile PhD in History, or a related field Demonstrated experience in
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Accountabilities PhD in biochemistry, Biomedical Sciences or Chemistry. Mass spectrometry-based proteomics. Data analysis of large proteomics datasets. Experience in cell culture and molecular biology. Languages
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, advanced co-culture organoid assays, and in vivo models to decode the mechanisms underlying CAF-driven CRC evolution. Access to single cell RNA sequencing and spatial transcriptomics data from active