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within the faculty participate in the programme. The course content is very broad and the specific subject of the dissertation depends on the institute. For research subjects, please see our website: http
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research, especially using modern technologies such as additive manufacturing (3D printing) and computer-assisted load analysis Expertise in the numerical simulation of realistic loading scenarios
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The Faculty of Engineering at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) invites applications for an Assistant Professor of Machine Learning in Digital Health (salary group W1
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English. You can write and defend your thesis in English or in German. The programme is designed to be completed in three years. During this time, defined milestones will help you and your supervisors
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conducted in German. Full-time / part-time full-time part-time (study alongside work) Programme duration 9 semesters or more Beginning Winter semester Additional information on beginning, duration and mode
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academic / professional and personal reasons for the choice of degree programme and for wishing to participate in the programme A current reference letter by a university professor that contains information
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opportunities within the university Yes Description of the above-mentioned funding opportunities within the university Please check our website on financial aid and scholarships: https://www.uni-stuttgart.de/en
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programme must be submitted online. For more information, please see the website: https://www.scripts-berlin.eu/birt/bgts/bgts-application/index.html All required documents must be submitted online by
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help them establish contact to potential supervisors for subsequent doctoral degrees. Who can apply? Chinese graduates from all disciplines are eligible to apply. What can be funded? A research visit as
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Programme for Women Professors Leibniz Collaborative Excellence Leibniz Transfer funding programme Selection process Funded Projects Open science OPEN SCIENCE Open Access Open and FAIR Data Citizen Science