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(university diploma or master's degree) in the field of geosciences, engineering or physics. Ideally, you have knowledge of numerical methods and experience with common programming languages (e.g. Matlab
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personal and professional growth, keeping employees up-to-date with the latest research and technology. Interdisciplinary collaboration: Our employees have the opportunity to collaborate with leading experts
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part of national and international networks, provides research infrastructure that is used worldwide, and supports young researchers in their careers. DIW Berlin is independent and, as a member of the
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highest level on the great questions affecting people, society, culture, the environment and technology — supported by experts in administration, IT and tech. Become part of LMU Munich! In the course
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collaboration, transdisciplinary cooperation with practice and an overall dynamic development characterize its research profile in the fields of education, culture, political science, management and technology as
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for scientific networking and professional development flexible working conditions – possibility of mobile working – support with childcare or caring for family members (certified by the "audit berufundfamilie
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. International networking and collaborations are regarded as an integral part of the PhD research experience and are explicitly encouraged (e.g. South America, Asia or Africa). The PhD process will be accompanied
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Description Within the Collaborative Research Center “Wave phenomena – analysis and numerics” (CRC 1173) we are currently seeking to recruit, as soon as possible, a Doctoral Researcher (f/m/d – 75 %) in Mathematics for the project “Quantized vortices and nonlinear waves” The CRC has been funded...
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able to experience hands-on testing of a high-speed and engine-representative compressor further increases of the efficiency and stability margin. The project is highly innovative, will generate
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Computer-adaptive methods and multi-stage testing Application of machine learning in psychometrics Predictive modeling of educational data Methodological challenges in cohort comparisons Advanced meta