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TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in Germany. It offers a modern, interdisciplinary, and international
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Research Associates (Doctoral Candidates) (f/m/d) within the Cluster of Excellence “The Ocean Floor"
of marine biogeochemistry, marine geosciences, marine (micro)biology and (paleo)climatology. The cluster offers a versatile qualification program in which doctoral researchers can strengthen their
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Teaching. The professor-ship should make a substantial contribution to teaching in the Master’s program in Marine Bi-ology. Supportive involvement in teaching related to nature and species conservation is
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State programme promoting young researchers (Tenure-Track Programme). The professorship is affiliated with the department of Medical Systems Biology (https://www.med.uni-wuerzburg.de/en/systemimmunologie
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(independently and in our team) involvement in teaching across different life science study programs at the Faculty of Medicine Required skills: Ph.D. (or comparable) in Bioinformatics, Computational Biology
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the Reinhart-Koselleck programme for innovative high risk-high gain research. Requirements: university degree in chemistry or physics and profound knowledge in computational and theoretical physics/chemistry
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and function of matter, from the smallest particles of the universe to the building blocks of life. In this way, DESY contributes to solving the major questions and urgent challenges facing science
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, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks Requirements: excellent university degree (master or comparable) in computer engineering or electrical
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at the University of Bonn, a W2 Professorship for Oral Technology is to be filled at the earliest opportunity. The future holder of the position is to represent Oral Technology within research and teaching. The
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. The research program may also involve a numerical simulation component. Your tasks #analyzing measurements of ocean turbulence using autonomous glider vehicles #use and develop machine learning methods