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and engineering disciplines Qualifications Applicants must meet the following criteria: A PhD in Accelerator Physics or a closely related discipline Documented significant experience innovating
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qualifications: PhD in medicine, natural sciences, or related disciplines. Documented experience in authoring scientific texts. Excellent spoken and written English skills. Experience with the full lifecycle
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"Beyond 3D points in Sparse Visual Mapping". Research subject The research area for the current call is computer vision and machine learning, with a focus on methods for visual localization and mapping
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and research in the field of chemistry. PLE has around 150 employees, of which around 65 are PhD students. The department offers a broad competence in areas such as chemical engineering, food technology
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with 25–30 active PhD students at the department. Work duties We are now looking for teaching assistants in FRTF05 Automatic control, basic course (study periods 1 & 2), FRTN65 Modeling and learning from
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and healthcare. The approach is interdisciplinary and may include concepts and methods from the humanities, social sciences or the arts, but also law, economics or engineering. The position reflects
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good ability to conduct, develop and lead teaching and other educational activities at different levels and using a variety of teaching methods ability to participate in supervision of doctoral students
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these initiatives, with a particular focus on applying experimental methods and advanced AI to analyse and understand complex societal phenomena. The research could revolve around the use of (Geo) AI to map and
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at different levels and using a variety of teaching methods This is assessed through a documented experience from teaching and supervising students at different levels. Your teaching ability will be assessed
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for school choice, segregation, resource allocation, and educational and career choices. The research group uses a wide range of methods, including field and survey experiments, register data studies, and