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Field
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-superconductors Enhancing multidisciplinary research on complex interfaces by fostering collaboration between state-of-the-art X-ray, neutron and muon techniques Presentation of data at meetings and conferences
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of the following areas will be a merit. Advanced AI methods development in Python or any other relevant programming language Computer Vision and image analysis Handling of large dataset Qualifications Applicants
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Requirements: A PhD degree in mathematics or related areas, with a strong background in topological data analysis (TDA) and machine learning on biomolecular data Proficiency in programming languages such as
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, brighter and carbon-neutral future. Our mission is to advance education, scholarship, knowledge and understanding through teaching and research, for the benefit of individuals and society at large. We have
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. Such strategies have been particularly evident in relation to Norwegian policy and presence in the Arctic. Ideally, the PhD candidate will focus on Russian subversion and information strategies directed at Norway
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will develop, implement, and apply advanced computational tools and reproducible workflows to interrogate large-scale, liquid chromatography–mass spectrometry (LC–MS)-based comparative metabolomics
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research is open; we are particularly interested in those working in the period between 1900 and the present. Open to scholars with PhDs in Science and Technology Studies and related fields whose research
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monitoring and subsea installations. The applicant for the PhD position is expected to contribute to existing and future projects with additional analyses and modelling based on collected data from
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, knowledge and understanding through teaching and research, for the benefit of individuals and society at large. We have put environmental sustainability and social justice at the heart of our strategy
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meetings. Qualifications: PhD in the social sciences in hand by July 1, 2025. Preference given to PhDs in Sociology or Religious Studies with dissertations based on primary field data. Demonstrated research