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Field
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criteria Machine Learning Expertise: A robust foundation in probabilistic modeling, Bayesian inference, deep learning, and/or anomaly detection Modeling & Simulation Experience: Familiarity with Building
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requiring long-term strategies of building trust to gain access to the object of research. Fieldwork may consist of deep immersion in one place or research in a number of sites – in either case, the onus is
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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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of Science and Freie Universität Berlin, Humboldt-Universität zu Berlin, and Technische Universität Berlin. The IMPRS-KIR traces the deep entanglements of knowledge and its resources from a long-term and
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the 01.10.2022. Your Responsibilities: You will work at the cutting edge of privacy-preserving deep learning research with a focus on one or more of the following topics: - Optimal model design for differentially
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atmospheres influence our affective life. It requires deep theoretical insight and experience with empirical research. The PhD student will conduct in-depth phenomenological interviews in Denmark, developing