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Associate Professor of Experimental Physics Focusing on AI-Based Research of Biomolecular Structures
demonstrate an excellent academic track record in research and teaching at the highest international standards. They should have substantial research experience abroad and/or international cooperations as
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have an exciting research plan with original goals for your future team. You should have an excellent track record during your PhD and Post-doc in genome biology and life sciences (or related fields
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profile You have an excellent Ph.D. and postdoctoral track record in the natural or life sciences, with an interest in the broader field of molecular systems biology. Applicants with a background in
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and/or methods development and propose an exciting plan of how to integrate your research with service. A track record of leading large projects, a team, or developing and managing a service-oriented
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strong motivation to lead in an open, collaborative, and interdisciplinary research environment. You hold a PhD in the life sciences and have developed a robust scientific track record spanning at least 10
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and circular economy You have successfully acquired and managed third-party funded projects and have a track record of publications in recognized, peer-reviewed journals Familiarity with programming
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and other scholarly activities, and should have a proven track record in the supervision of doctoral theses and career development of young researchers. They should be interested in communicating
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using common frameworks (preferably react, nextJS) Previous experience with Protege or similar tools for semantic modeling and web-based services for managing software (version control, issue tracking, CI
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creating corresponding user documentation for scientific software Practical knowledge in maintaining open source software projects using platforms for version control, issue tracking, and CI Experience in
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with the latest sensors (camera and LiDAR sensors), is available for the work. What you will do – development of algorithms for 3D multi-object tracking based on heterogeneous sensor data fusion