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Participate in meetings to discuss the AQPU plan together with the team Help your peers in solving their challenges in reaching the milestones including the supervision of BSc theses and possibly of PhD and MSc
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. Desirable criteria Experience working with generative models or large language models Experience with GPU-based model training or cloud computing Knowledge of synthetic biology or regulatory sequence design
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related discipline and have begun to establish a strong research profile, evidenced by a strong, well-cited publication record. Proficient in Python, R, BASH and/or other relevant programming languages, you
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. Research competence & initiative demonstrated through international publications in peer relevant media. Excellent command of English, both written and spoken You are goal-oriented and have a high motivation
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or in national administrative or legal practice are of advantage. Excellent knowledge of German and very good knowledge of English (C1), knowledge of another foreign language is an advantage. You exhibit
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in related program areas to gain exposure to and build knowledge on experimental/research activities and approaches, in order to improve conceptual development and industrial implementation. Identify
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, spiroergometry, and dietary assessments Excellent German and English skills, both written and spoken Strong team player with excellent social and communication skills Resilience and high level of motivation What
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the Department of European and Comparative Literature and Language Studies, characterized by a broad range of research interests within Finno-Ugric studies in the wide sense of the word and by intensive
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with the possibility of renewal. This project addresses the high computational and energy costs of Large Language Models (LLMs) by developing more efficient training and inference methods, particularly
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, and implement whatever is most suitable. Possibility to take part in publications as a research engineer. Provide one-on-one and group research support from a software, programming, Linux, data, and