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engineering, acoustics, machine learning or similar; Solid mathematical and analytical skills, including signal processing, optimization, machine learning or information theory; Experience in programming, e.g
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, learning, and inference for classical and quantum data. At the Technical Faculty of IT and Design, Department of Computer Science, one or more PhD stipends/Integrated PhD stipends in representation
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population data will be considered a strong advantage. The ideal candidate is comfortable learning new analytical methods and working with large and complex datasets. Qualification requirements PhD stipends
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reliability. Prospective applicants for this PhD proposal should have the following qualifications: M.Sc. degree in communications engineering, mathematical engineering, electrical engineering, computer