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within the group and across Research & Development. Who You Are: PhD in Computational Biology, Computer Science, Applied Mathematics, or similar field Demonstrated record of innovative scientific
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of Oslo. Job description A fully funded PhD position is available on the development of spatiotemporal statistical modelling of climate-sensitive infectious diseases, with a particular emphasis on Bayesian
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the candidate is admissible to UiA’s PhD programme at the Faculty of Social Sciences , and that the Department of Sociology and Social Work or CeDIT currently has a thematically relevant advisor available
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PhD Research Fellowships: Artificial Intelligence Adoption, Sustainable Finance, and Twin Transition
, Sustainable Finance, and Twin Transition Apply for this job See advertisement About the positions Inland School of Business and Social Sciences , The PhD programme Innovation in Services in the Public and
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through a PhD education leading to a doctoral degree. Starting date for the positions is no later than 01 Januray 2026. The hired candidates will be admitted to the PhD program in Science and Technology
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the third and fourth years of the degree programmes, from spectral theory, groups and geometry to fluid mechanics and from mathematical ideas in biology to cosmology. Research funding in the department from
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of Computing and Digital Technology is a thriving, vibrant, and inspiring learning community committed to excellence in research, high quality teaching and impactful industrial engagement. Building on continuous
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development, research delivery, and dissemination; leading/supporting grant applications to prestigious funders; contributing fully to our ARC Academy training programme. The postholder will also support the
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, the flagship programme of the Newcastle Health Research Partnership. In addition to the Newcastle PSRC, the postholder will have an academic home at the Newcastle University Population Health Sciences Institute
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-throughput functional screens, and computational biology. They will deploy single cell genomics and spatial transcriptomics approaches to uncover new tumor-TME communication patterns, deploy therapeutic