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application! Work assignments We are looking for a postdoc who is motivated not only by solving established problems, but by exploring new ways of formulating them, incorporating their own ideas and experience
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actively for equality and diversity. You will, therefore, within the framework of this employment, undergo an introductory course focusing on equal conditions. The person we need Only those who have been
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application! About the job We are looking for up to 10 teaching assistants (amanuenses), who, when needed and agreed upon, will assist course leaders in their teaching activities. Teaching assignments may
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to the application. Of merit is examination and course coordination responsibility; supervision of student theses; documented contributions to course design; undergraduate teaching experience from other areas
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understanding of ionic and molecular transport at the implant-tissue interface and in the microenvironment around the implant. This will enable us to predict how these transport properties shape electrode
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application! We are announcing a PhD student position in Computer Science within CUGS Research School in a joint effort with Cybercampus Sweden , formally based at the division for Cybersecurity at Department
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application! We are looking for two PhD candidates in the research environment “Culture and Society” with a focus on Digital Society, Infrastructure, Legacies. Your work assignments We are advertising two PhD
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application! We invite applications for a fully funded PhD student position to join the research group of Andrew Winters to work on challenging problems in Computational Mathematics for accurate and reliable
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application! We are looking for a postdoctoral researcher to work on the fundamentals of knowledge graphs and virtual data integration. Work assignments You will actively participate and lead work tasks in two
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application! We are looking for a PhD student in biomedical engineering with a focus on deep learning for medical images Your work assignments The position focuses on developing methods for federated learning