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Field
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thesis has been approved, along with a documented indication of the expected date of formal graduation. It is the responsibility of the faculty mentor to verify this documentation. The documentation must
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computer programming in R and Python *Formal training or experience applying quantitative and spatial methods to human-environment questions *Excellent academic writing and communication skills in English
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accelerators, and of applications exhibiting these patterns in performance-critical hotspots; Development of methods to streamline programming AI-enhanced systems, taking into account partitioning / mapping and
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/MS for example) Advanced knowledge in research design and methods (running extensive experimental studies) Familiarity with practices of transparency and open science Strong interpersonal and
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essentially new methods to automatically verify cyber-physical systems. Because none of the existing methods and tools for the formal verification of cyber-physical systems are fully automatic, these methods
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explores novel aggregation methods at the intersection of AI safety, computational social choice, and judgment aggregation, aiming to formally integrate multi-stakeholder preferences into AI system design
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/MS for example) Advanced knowledge in research design and methods (running extensive experimental studies) Familiarity with practices of transparency and open science Strong interpersonal and
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imaging methods complemented by in house X-ray imaging (axia.au.dk). Additionally, X-ray fluorescence, scattering, diffraction-based imaging will be employed. The biological and bioinspired materials group
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. The successful candidate will contribute to further advancement of the experimental setup and utilize electron- and light-based advanced methods to conduct materials and surface science research. Duration: 12
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imaging methods complemented by in house X-ray imaging (axia.au.dk). Additionally, X-ray fluorescence, scattering, diffraction-based imaging will be employed. The biological and bioinspired materials group