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learning, AI interpretability, formal verification methods, modeling emergent risks from AI R&D automation. Candidates are encouraged to interpret these subject areas broadly. Fellows will have access
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in relevant laboratory methods. Contribute to a safe, collegial, collaborative, and intellectually engaged laboratory environment. Anticipated start date: December 1, 2026, or a mutually agreed date
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guidance throughout the duration of the fellowship. Qualification requirements Formal qualifications Education equivalent to five years at university level in Norway, with two years (120 credits) at Master’s
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of the sessions as technical and scientific support, recording the methodologies applied, recurring questions and exercise results for subsequent analysis. Support to participants in applying econometric methods
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of the sessions as technical and scientific support, recording the methodologies applied, recurring questions and exercise results for subsequent analysis. Support to participants in applying econometric methods
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methods appropriate to the research questions and data. Mixed-methods, qualitative, participatory, design-based, or intervention components are also welcome where they strengthen the overall project
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techniques such as electrochemistry, AFM, SPR, QCM-D, CD, FTIR, fluorescence microscopy, or related methods is desirable.
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resulting from the contributions provided for this Social Insurance, according to the Statute of the Research Fellowship. Selection process Selection criteria: The applicable selection methods will be
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these methods to address challenges in scientific discovery and precision medicine. We seek highly-motivated applicants with background in one or more of the following areas: agentic AI, geometric deep learning
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possess the teaching/pedagogical qualifications that meet the requirements for an associate professorship (incl. formal training), the department shall facilitate the acquisition of such qualifications