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Skip to main content. Profile Sign Out View More Jobs Research Assistant: register data from Statistics Denmark - DTU Management Kgs. Lyngby, Denmark Job Description The Division for Climate and
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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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Skip to main content. Profile Sign Out View More Jobs Research Assistant in statistical analysis of hybrid work data sets - DTU Engineering Technology Ballerup, Denmark Job Description The Research
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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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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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beyond. Hence, we seek a proactive candidate with a strong background in statistics and economics. Your primary tasks will be to: Design workflows for quantitative societal sustainability assessment of low
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The National Centre for Register-based Research (NCRR) seeks to hire one or more research assistants for projects focused on psychiatric epidemiology and statistical genetics. NCRR is part of Aarhus
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genetics, animal breeding, statistics, or a related field. Proficiency in statistical analysis of genetic data related to insect breeding and experience in developing insect breeding strategy. Experience
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of survey research, from planning and ethics approval, through pilot work and data collection, to statistical data analysis and write-up. Qualitative research skills and experience are an advantage but not
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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