30 parallel "Computer Vision Center" "Computer Vision Center" PhD positions in Switzerland
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-enhancing technologies, and privacy-preserving authentication. Contribute to the development of secure and privacy-preserving protocols. Support and assist in teaching courses on computer security and
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applied, data-intensive research projects Your profile An above-average degree in economics, statistics, data science, quantitative marketing, computer science, or related fields Strong interest in
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Center for X-ray Analytics , we develop and characterize advanced nanosystems for biomedical applications. Combining expertise in nanomaterials, colloid and analytical science, cellular biology and
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in business administration, economics, psychology, computer science, data science, or related fields Strong interest in scientific questions related to the fields of digital marketing and technology/AI
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profile Excellent Master's degree in Computer Science, Software Engineering, or a closely related field. Strong interest in research in one or more of the areas of software engineering, programming
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participate in grant writing and proposal development activities Your profile You have a university-level master's degree in computer science Desirable: previous publications in journals or
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computer that can solve real-world problems will require the integration of many highly coherent qubits. Hole-spin qubits in planar germanium quantum wells are among the most promising candidates for this
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regular faculty, and gradually progresses to the latter. Instructors are expected to be able to teach courses in English or French. Applicants should have a PhD in Mathematics or in Computer Science
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Engineering, Mathematics, Computer Science, or a related quantitative field A strong mathematical background, including familiarity with optimization, probability, and the analysis of mathematical models A
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background, and an outstanding MSc degree in Engineering, Computer Science, Physics, Applied Mathematics, or a related field. You should be proficient in or willing to learn generative deep learning – in