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Field
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groups — building skills, learning new techniques, and connecting with other scientists. Scientific writing & communication: In your first year, you’ll join a dedicated writing workshop to build strong
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research excellence and the ability to pursue a doctoral degree at TUM Documented experience in machine learning and/or natural language processing with deep knowledge of LLMs, RAG and agent-based AI systems
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. Interdisciplinary work is encouraged so that junior researchers can assess the value of their own work in relation to the whole. e-Learning “Good Academic Practice” “Studying and Then Earning a Doctorate?” For
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disciplines (Master's, "Diplom" or teaching degree) Language requirements Fluency in German or English. If you do not yet speak German, you are expected to acquire basic skills during the first year of
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research on exciting projects and develop customised products and services for our clients from numerous industries and the public sector. The overarching topics at Fraunhofer ITWM are machine learning
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University of Education Freiburg • | Freiburg im Breisgau, Baden W rttemberg | Germany | about 2 months ago
on learning and teaching foreign languages in these regions and to qualify academic staff to gain proficiency in the fields of scientific methods and methodology in foreign language pedagogy, linguistics
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international conferences. This can provide opportunities for networking and learning from other researchers in your field. Extracurricular Seminars and Trainings The in-house umbrella organisation INGENIUM
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with other doctoral researchers as well as with supervisors over an extended period of time. The research classes are based upon the cooperative work of the group and the principle of peer learning. In
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, in educational and research institutions. Main features: Research-based teaching and learning – featuring intensive training and cutting-edge research projects in pure and applied mathematics
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, the university is actively part of regional, national and international research networks. The university is committed to the principle of unity between research and teaching. Students acquire knowledge, expertise