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(diplomas) and a full CV including information indicating experience in industry co-operation and/or international co-operation. A brief description of research profile, research publications, research
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, computer engineering, computer science, data science, mathematical engineering, robotics, or a closely related field. The candidate should have solid mathematical and analytical skills and a strong interest
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related field at the level of a master degree Programming skills (Python) and experience with common machine learning platforms Experience with deep learning, computer vision, medical image analysis
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an important challenge in Human-Computer Interaction research: how can we create a proxy for a remote physical object that does not replicate, but extends the experience of interacting with the object itself
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study pre-PhD. Development, teaching, and operation (40%) Contribute to our extensive portfolio of tasks linked to the ongoing digital transformation of the degree programs at Aarhus University
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of the contemporary extended enterprises; the principles of business process engineering and value engineering, and the mechanisms of strategy, organization design and effectiveness. Your competencies We are looking
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deep learning, computer vision, medical image analysis or unsupervised learning is an advantage. English language skills, both written and spoken Qualification requirements PhD stipends are allocated
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to the 3 + 2 Bologna process) have received the grade of 10 (or equivalent) for the master's thesis according to the Danish 7-point grading scale (https://ufm.dk/en/education/the-danish-education-system
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The department will give priority to applicants with high grades from their universities. To be considered the applicant must: have a basic education at master's level (corresponding to the 3 + 2 Bologna process
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Postdoctoral position for the project Human AI Collaboration: Imaginaries, Interventions, Interfaces
the stated framework of the research project (max. 1-2 pages). Please note that although the application process can be completed on the Aarhus University system without uploading publications or a teaching