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Job Reference: 1044217 About the Role: Join a pioneering national research initiative at the intersection of geochemistry, data science, and critical minerals. As an AuScope EarthBank Fellow, you will play a key role in a project investigating the periodicity of critical mineral formation across...
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will make one discovery-scientist post. You will have a track record working on normal breast tissue in vitro modelling and already have an established network of local collaborators, including clinical
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, engineers, computer scientists, nuclear medicine physicians, …) towards the overall aim of enabling translational and physician-in-the-loop AI for medical imaging. Our research team is multicultural and
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excellence, setting standards for rare disease management and offering training opportunities for specialist clinicians and clinical scientists. The LifeArc and MDUK-funded Translational Rare Disease Centre
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Applications are invited for the prestigious Eric and Wendy Schmidt AI in Science Fellowships, a program of Schmidt Sciences, commencing 1 September 2026. This 1-year appointment at Imperial College
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across six sites in Heidelberg (headquarters), Barcelona, Cambridge, Grenoble, Hamburg and Rome. Our mission is to perform basic research in molecular biology; train scientists, students and visitors
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to teaching activities and provide support to PhD students and research assistants in the programme. You may be a great fit if: You are a skilled statistician with a PhD in statistics, applied mathematics, or a
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information about AbbVie, please visit us atwww.abbvie.com . Follow @abbvie onX ,Facebook ,Instagram ,YouTube ,LinkedIn andTik Tok . Job Description Program Overview AbbVie needs outstanding individuals willing
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information about AbbVie, please visit us atwww.abbvie.com . Follow @abbvie onX ,Facebook ,Instagram ,YouTube ,LinkedIn andTik Tok . Job Description Program Overview AbbVie needs outstanding individuals willing
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Collaborating closely with data curators, multi-omics data scientists and AI engineers to integrate and enrich disease datasets, and test and validate models Applying hybrid modelling approaches to limited data