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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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· A scientific CV with contact details · List of publications (and patents, if applicable) · Contact details of 2 references Please apply ONLINE formally through the HR system
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productively with both the CAISA research team and external organisations and institutions experience with mixed methods Furthermore, it will be considered an advantage if applicants can document: experience
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Analyze and assess risks of de-anonymization, including researching current de-anonymization strategies Investigate synthetic data generation methods and their utility Deploying and benchmarking the above
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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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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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, Luxembourgish and / or French will be considered an asset Interest in empirical social research, excellent command of quantitative and / or qualitative empirical methods; openness to mixed methods research
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methods such as gas chromatography, Karl-Fischer (for water), titration methods for TAN/CAN, elemental analysis etc. Synthesis and characterization of catalysts. Writing of scientific papers and attending
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supervision conferring with higher levels only in unusual situations. 8. Performs other job-related duties as required. Benefits: Please visit the following site for a complete list of benefits offered
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participation in national and international conferences is integral to the job. Furthermore, participation in supervising BEng, BSc, and MSc students is expected. As a formal qualification, you must hold a PhD