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our research group, Machine Learning and Computational Intelligence (MaLeCI), which is a dynamic and diverse team of talented and highly-motivated researchers conducting cutting-edge research in Machine
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dairy cattle. Tasks and responsibilities Develop statistical and machine learning methods to exploit ancestry patterns over the genome of individuals. Develop methods for simulation and analysis
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/mechanical engineering, computer graphics/vision, machine learning, or other related skills that are useful for fabricating new types of physical objects and interfaces excellent programming skills Your
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research centre. Research at CFIN include fields such as cognitive neuroscience, neuroimaging, machine learning and biophysics. Investigators at CFIN are supported by state-of-the-art research facilities
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variety of countries, experience with computer assisted coding of big chunks of text and experience with large-N analysis of cross-national data will be positively evaluated. The successful applicant will
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supported cooperative learning documented by a PhD dissertation and/or research publications. experience in the self-directed management of research projects experience in interdisciplinary research projects
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, and machine learning methods will be highly desirable. Experience in development and use of EC-Earth (European Community Earth System Model) in relation to aerosols and clouds will be highly desirable
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, students, and academic staff to gather feedback and insights on the use and effectiveness of AI-driven educational tools. - Stay abreast of advancements in AI, machine learning, and computational
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analyses using Danish register data and/or large genetic datasets. This may include genetic analyses, causal inference, epidemiological analyses, and clinical prediction modelling using machine learning
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applicant will be expected to teach in English. Qualifications Applicants must have a PhD degree or document equivalent qualifications in a relevant field related to STS, information studies or neighbouring