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, structured PhD program for all doctoral candidates working at LIV with binding guidelines developed based on the Leibniz Association's guidelines for graduate education. Our program offers multidisciplinary
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only in English. Full-time / part-time full-time Programme duration 6 semesters Beginning Winter semester Additional information on beginning, duration and mode of study Successful applicants will then
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equivalent degree with a specialisation in natural or computer science. Language requirements English is the programme language. Good written and spoken English is essential. Application deadline Application
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represent stakeholder preferences. The integrated Research Training Group (RTG) will provide doctoral researchers with an attractive qualification program, foster networking, enable internationalization and
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German Institute for Economic Research (DIW Berlin) • | Berlin, Berlin | Germany | about 21 hours ago
engineering, statistics, or quantitative social sciences) may also fulfil requirements for the programme if applicants have sufficient background knowledge in economics. Applicants whose native language is not
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(100%). Participants can write the PhD thesis in English or German. Programme duration 6 semesters Beginning Only for doctoral programmes: any time Tuition fees per semester in EUR None Combined Master's
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) Microeconomics / Applied Economics The initial appointment will be 2 years with the possibility of extension. Salary is in accordance with the German State Regulated Public Salary Scale (starting at TV-L E13 2/3
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students. Programme duration 6 semesters Beginning Winter semester Application deadline 15 July Tuition fees per semester in EUR None Combined Master's degree / PhD programme No Joint degree / double degree
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in the language agreed upon with his or her supervisor. Full-time / part-time full-time Programme duration 6 semesters Beginning Winter semester Application deadline The deadline for applications is 1
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knowledge of quantitative methods, particularly in statistics and econometrics; experience in machine learning is a plus Background in business/management/behavioral science Experience with programming