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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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/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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in Cambridge. The mission statement of the group is "developing statistical methods to use genetic variation to answer clinically important questions about disease aetiology and prevention". The three
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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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Job Description We offer an exciting postdoc position dedicated to developing methods for detecting performance disparities in foundation models for fetal ultrasound and understanding what causes
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and brain that explain vision loss, building on our previously-developed method linking clinical, neural and behavioral data (Allen et al., 2018; Miller et al., 2019; Pedersini et al., 2023). We combine
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considered an asset Training and experience in quantitative empirical methods Good command of multivariate and complex statistical methods International publications in peer-reviewed journals and / or book
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to develop innovative methods and actionable tools for detecting, analyzing, and preventing vulnerabilities in supply chain systems, leveraging state-of-the-art AI and ML techniques to improve overall security
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perspectives on large language models Statistical learning theory and complexity analysis Automated theorem proving and formal methods Random matrix theory and its applications in modern AI systems This position