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methods for studying somatic mutations at increasing scale and precision. In close collaboration with the Huang lab and others, we are 1) Developing new experimental and computational tools to identify
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. Teaching: Whilst no formal teaching commitment is required in this role, the Research Fellow will have the opportunity to contribute to the development and delivery of teaching materials and training modules
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involves formalization in type theory and the mechanization of results using interactive theorem provers. The project welcomes a broad range of perspectives across functional-imperative programming
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UiO/Anders Lien 17th August 2025 Languages English English English PhD Fellow in Innovation Studies (AI) Apply for this job See advertisement Job description One PhD research fellowship (SKO 1017
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new models of examining the data To provide teaching to junior staff in the lab in neuroscience-related research methods, especially in pre-processing and processing of EEG data from infants/children
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of sedimentology, geochemistry, and microbiology, and general use of destructive, extraction-based methods that are designed for the analysis of large sediment samples. These bulk methods are quantitative but
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include an interview. Applicants must hold a two-year Master’s degree (or equivalent qualifications) and meet the formal requirements for admittance to the Faculty of Social Sciences’ PhD program. The
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interested in applicants who use advanced quantitative methods, including computational modeling, machine learning, and/or analyzing structural and functional neuroimaging data. Specific activities may include
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Qualifications PhD in public health or related field obtained within the last five years. Proven ability to thrive in a collaborative, mixed-methods research environment. Strong personal motivation, self
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research teams to drive impactful studies Mentor trainees in different aspects of clinical research Minimum Qualifications PhD in public health or related field obtained within the last five years. Proven