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available for a period of 3 years starting January 1, 2027. The PhD student will be enrolled in the doctoral programme in Health Care, Health Promotion and Organizations at the Faculty of Medicine. Applicants
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The Department of Electronic Systems at The Technical Faculty of IT and Design invites applications for a PhD stipend in the field of secure machine learning within the general study programme
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Assistant Professor in statistics for the development of privacy-enhancing techniques in health care
Programme, “Synthetic health data: ethical development and deployment via deep learning approaches (SE3D)” which is a collaboration between Head of Center and Professor Martin Bøgsted, Center for Clinical
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possible thereafter. The appointment is for a period of three years. The successful candidate will be enrolled in the PhD programme in Biomedical Engineering and Neuroscience at the Faculty of Medicine
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positive written assessment of their teaching qualifications. Who we are The Department of Clinical Medicine provides research-based teaching across all disciplines of the medical degree programme and
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• Participate in the department’s research environment • Complete a PhD training programme • Teach at one or more of the department programmes Your main task as a PhD student will be to develop and complete a PhD
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patterns representing health incidents and the development of privacy-preserving methods for visualizing health data. What you will gain: Strong expertise in statistical and computational methods for privacy
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At the Technical Faculty of IT and Design, Department of Sustainability and Planning (PLAN), a PhD stipend is available within the general study programme Planning and Development. The stipend is
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project-based learning, pedagogical development and institutional capacity building. The work will include research support connected to projects within the Global PBL Certificate Programme. Concrete tasks
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will gain: Strong expertise in statistical and computational methods for privacy Experience working with unique, real-world health data Collaboration with an interdisciplinary research team across data