278 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" uni jobs in Denmark
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in the fields of: Construction Management and Lean Construction. Production Planning and Control. Data-driven analytics and management of construction operations. Construction Informatics, including
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Partner Programme . You can also find information about the taxation aspects of international researchers’ employment by AU . An appointee who does not speak Danish will be required to acquire proficiency
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more about the department at www.es.aau.dk. Your work tasks The PhD project is part of a bigger Novo Nordisk Foundation (NNF) New Exploratory Research and Discovery grant entitled: Information Theoretic
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highly skilled employees. More information can be found here . What we offer Work with advanced analysis equipment An exciting interdisciplinary environment with close collaboration between laboratory
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-drive systems. Across the above areas, you are expected to contribute to model-based and data-driven/AI-based methods, including digital twins, physics-informed learning, data analytics, and AI-assisted
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quantitative analysis of register, survey, and patent data to various qualitative methods. If you have an interest in, or experience with, novel computational methods such as NLP, machine learning, and AI
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theoretically. Further information can be obtained in the department’s qualification guidelines. Successful candidates will be expected to teach and supervise students in our business administration programs
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Professor in AI-driven patient stratification and microbiome-based interventions (combined position)
data Explorative Network) , Odense University Hospital (OUH), respectively. The position is vacant as soon as possible, and the two 50% positions are considered as one entity (= full-time). Job
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Aarhus University, and the place of work is Department of Biological and Chemical Engineering, Aabogade 40, 8200 Aarhus N., Denmark. Contacts Applicants seeking further information regarding the PhD
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we expect: Qualifications The candidate must have a PhD degree at the time of employment. We value candidates who combine strong experimental skills with an ability to integrate data-driven approaches