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program. Academic staff contribute to the teaching. English is the preferred language in the laboratory, at meetings and at seminars. The department employs approx. 500 people from all over the world, and
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, nursing science, and related methods, and for a significant part of teaching in the medicine program. We are firmly rooted in our academic disciplines and actively foster interdisciplinary collaboration
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Genetic Improvement of Dairy Cow Longevity, Using Large-Scale Body Weight Data from an AI-Camera ...
Applicants are invited for a PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Quantitative Genetics and Genomics programme. The position is
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Two Senior Innovation Coaches (specialkonsulent) for Early-stage Medical Technology Innovation Teams
tools and our teaching methods. We expect you to bring in to use your existing tools and methods where this benefits the program and we expect you to adopt the corner stones of our needs-driven innovation
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of this position is to strengthen our research in statistics, preferably within the current research areas of the department. This includes both fundamental and applied research (e.g., statistical methods
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, agroecology, or have similar experience Document experience in scientific writing with numerous papers in high-quality journals or other high-quality publication channels Possess an excellent H-index (depending
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. We have a keen interest in health promotion, prevention and treatment, and use methods from epidemiology, statistics, public health science, health services research, health science and humanities and
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and relevant industry experience will be prioritised; familiarity with Horizon Europe Programme and previous experience under this programme; strong communication and personal interaction skills
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science (PDS) within the area of pharmacoepidemiology and pharmacovigilance. It will be the responsibility of the candidate to establish a portfolio of research within AI methods in observational drug
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of this position is to strengthen our research in statistics, preferably within the current research areas of the department. This includes both fundamental and applied research (e.g., statistical methods