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within the Data Science & AI division (DSAI). With 30+ nationalities and strong industry/academic ties, we offer a dynamic, collaborative ecosystem. The AI and Machine Learning in the Natural Sciences
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digital twin framework, adaptable to: The level of detail available for ship modelling, The quality of risk-related data, and Quantified model and data uncertainties. The project will advance knowledge
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develop analysis pipelines to analyze high dimensional spatial and single-cell data of cancer and immune tissue from patients and pre-clinical studies and should have a strong background in both
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work aimed at combining imaging techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. To be a postdoc fellow at the AMBER programme you
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to be awarded, a PhD degree or equivalent in biochemistry, cell or molecular biology, genetics or a related discipline. We are seeking highly motivated applicants with practical experience in
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stiffness or stretchability. You will collaborate closely with PhD students and Postdocs in our group as well as external partners to study the mechanical, electrical, and electrochemical properties
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both competitive in peacetime and resilient in times of crisis. For more information, visit FORCE – Centre for Food Resilience and Competitiveness. Subject description The postdoctoral position focuses
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, as well as handling bioinformatics tasks such such as running analysis pipelines, performing quality control, and conducting downstream data analyses. You are expected to actively contribute to method
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also include technique development work aimed at combining imaging techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. To be a
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ecology. Your profile The successful candidate shall have a PhD degree in environmental sciences or a related field with a good understanding of soil and aquatic ecosystems, biogeochemical cycling