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Field
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analysis of large data sets, statistical modeling, and knowledge of at least one programming language (e. g.: R, Python and/or Julia) are required. Experience in machine learning and image recognition
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of research results or willingness to acquire such experience willingness to conduct a research stay for several month at another institute very good knowledge of MS Office, including Word, Excel and PowerPoint
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and teach courses in the research areas of the professorship, in particular the political economy of technological change. Actively participate in the intellectual life and research activities
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courses in HDS domains to learn advanced health data sciences methods that they will later apply in a practical research setting for their individual research projects. Research: Interactive seminars and
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formations are of growing economic and societal importance. By participating in a number of externally funded projects, doctoral candidates learn to perform independent scientific work. Through active
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for the modeling and simulation of 3D reconfigurable architectures e.g. based on emerging technologies (e.g. RFETs, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks
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to environmental cues. Innovation drivers include the development of advanced technologies and the full integration of complex computational approaches to answer relevant biological questions. To learn more about
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work together, in order to learn from one another and generate new knowledge and new methods to create a better quality of life in our world. DWI offers you a wide range of possibilities to develop
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work together, in order to learn from one another and generate new knowledge and new methods to create a better quality of life in our world. DWI offers you a wide range of possibilities to develop
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learning is pursuing the goal to collect activities and information on AI in order to explore and shape the rapidly growing field of AI together and to make it accessible to our students entering the field