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are looking for a highly motivated post-doctoral candidate interested in advanced health data interoperability and harmonisation, federated data analysis and the development of next generation AI-based research
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-preserving machine learning (e.g. proving model integrity or fairness without revealing training data) Scalable ZK-proof constructions for federated and decentralised AI pipelines Formal security analysis
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the Department of Mathematics and Statistics the main research areas in mathematics and applied mathematics include discrete mathematics, theoretical computer science, number theory, analysis, optimization
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these efforts, we aim to accelerate the translation of molecular and clinical insights into tools that improve patient outcomes. More information about the lab can be found here: https://www.nathlab.org As a
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variety of cutting-edge techniques including behavioural analysis, functional imaging, and brain stimulation. Together, these are used to provide a picture of the unique and privileged processing
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: https://neurock.cems.umn.edu/ Candidates are expected to lead scientific research efforts, mentor and collaborate with others, give scientific presentations and write scientific reports and manuscripts
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Assistant postdoctoral 56 Faculty of Mathematics Job vacancy starting: 01.10.2026 | Working hours: 40.00 | Classification CBA: §48 VwGr. B1 lit. b (postdoc) Limited contract until: 30.09.2029 Job ID
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attention to detail, strong qualitative analysis skills, and the ability to apply complex coding schemes consistently. Your ratings establish the validity benchmark against which AI scoring will be evaluated
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technologies, and the use of data to support decision-making and improve performance. The research will include qualitative and quantitative data collection and analysis, case studies, document analysis, and
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lab/field personnel in research. Responsibilities: Responsible for data collection, cleaning, compilation, and analysis. Develops data-driven visualizations and reports to support research and decision