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University, a leading international research group investigating psychiatric epidemiology and statistical genetics. The Centre has a strong track record in collaboration with other Danish researchers and with
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Postdoc in statistics to develop Bayesian privacy metrics for synthetic health data (2024-224-05725)
on Bayesian statistics and apply them in several real-world settings of important clinical relevance. The postdoc will be responsible for developing the area with a group consisting of a PhD student, a data
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mitigation strategies. Tasks and responsibilities: Using statistical signal processing methodology to develop methods of fault detection for snifferes measurement system. Develop methods of noise filtering
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surface structure of single nanoparticles by integrating atomic-scale simulations, statistical methods, and TEM imaging. Exploring the use of Bayesian statistics to understand experimental data and improve
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opportunities these signals offer for modeling and prediction. Our research is based on statistical machine learning and signal processing, on quantitative analysis of digital media and text, on mobility and
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opportunities these signals offer for modeling and prediction. Our research is based on statistical machine learning and signal processing, on quantitative analysis of digital media and text, on mobility and
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statistical modeling and methods development to experimental hypothesis evaluation and clinical translation. There are also close collaborations with the wet-lab and clinical groups at the department ( https
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or equivalent in bioinformatics or related fields, e.g. computer science or statistics. Candidates finishing their PhD before May 2024 will also be considered. We require: Experience in machine
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( https://biomed.au.dk/demontisgroup ). You will perform statistical analyses of large-scale genetic datasets of ADHD and weight related phenotypes derived from diagnosed cohorts or population-based data
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languages (eg, R, Python), implement statistical associative models (eg, GLMM), as well as experienced in simulation development (eg, multi-agent based models). You will also work with stakeholder engagement