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this PhD project are: Develop strategy for individualized earphone-based sound, which includes adequate representation of the physical environment(the acoustics of the listener's ear and the room in
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of the developed cavitation model with acoustic radiation models, validating against experimental data. Required Qualifications A relevant educational background within Mathematics, Physics, or Engineering, with a
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Technology at the Faculty of Medicine, which does multidisciplinary research and teaching in the area of health science and technology(e.g. medicine and biomedical engineering). The strategic focus
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We seek PhD students that will contribute to new generations of scalable, model-based tools for cyber-physical systems based on a mathematical sound foundation, that enables trade-offs between
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optimization. The main task of this PhD student is to develop new simplified electrochemical models that can be used in physical-aware AI health management. The models should be verified in terms of accuracy
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student is expected to contribute actively to the research and teaching activities of the IKE research group. In addition to writing scientific articles, the PhD student is expected to collaborate with
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, please contact head of department, professor Michael Baggesen Klitgaard at [email protected] For general information about the application process etc., please contact Lene Møller, e-mail: lml
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activities, coded as Action Units(AU) in a facial action coding system. Based on existing datasets, this PhD project will strive to automate this process. First, the focus will be on research and development
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Professor Mette Simonsen Abildgaard and Postdoc Laura Kocksch in the project’s initial phase. An online information meeting will be held on Wednesday, May 22nd at 4 pm CET to provide potential applicants
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There is a huge potential for using artificial intelligence(AI) for improving diagnosis and treatment of many diseases. Large amounts of clinical data are needed to train useful AI systems. However