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Field
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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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methods, including Mendelian randomisation, to identify candidate mechanisms linking circadian misalignment and sleep disturbances with cardiometabolic disease. The successful applicant will join an
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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 for subsurface sensing and characterization. -Present research outcomes at conferences and contribute to peer-reviewed publications in geophysics and computational science. -Collaborate with team
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health economic impact. Further detail: We have demonstrated proof of concept on the lab bench of a UV ‘elucidation’ method. This identified previously missed bone fragments that had passed manual
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experience in machine learning methods, tools, and platforms. Proficiency in Python, with demonstrated software development experience. Hands-on experience in MLOps, including the design and deployment
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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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research team to contribute to projects at the intersection of AI/ML, real-world data, and health outcomes. The Postdoctoral Researcher will play a key role in developing and applying cutting-edge methods
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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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disparities for communities and populations. Candidates will receive mentorship and training in precision health, including advanced statistical methods focused on predictive modeling in relation to response