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compilers Knowledge of machine learning and artificial intelligence techniques, including computational aspects of large-scale models (e.g. foundation models) Specific technical knowledge in selected areas
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and especially regression-based models, such as linear regression or structural equation modelling. Furthermore, qualitative comparative analysis (QCA) and machine learning approaches could be applied
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and control and software development. All topics have a heavy focus on AI-based methods (e.g., machine or deep learning) and their real-time execution on real robot systems. Research takes inspiration
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and the Neuroscience Center or the Department of Computer Science, respectively. Who can apply The candidates are expected to have: a PhD degree in one of the relevant fields, an ability to conduct
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applying tools from computer simulations and machine learning. The position is fixed-term and the starting time is 01.06.2025, or as soon as possible thereafter, based on mutual agreement. The contract
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problem purely from a machine learning perspective, without any human-in-the-loop consideration. The primary objective of this doctoral project is to address the complementary roles of humans and automatic
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, are our top priorities. Expertise in machine learning and human omics data analysis is highly advantageous. The ideal candidate should demonstrate a high level of independence while also valuing
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a related quantitative field. The position requires: Programming Proficiency: Experience in R and python programming, including data science and Machine Learning packages Experience in R and python
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fiber spinning machine, carding, roving, ring spinning, circular knitting machine, padding mangle, laboratory dyeing machine, universal mechanical testing machine, textile printer, and ash-/rub
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encourage qualified candidates from all backgrounds to join our community. The together and with passion, we research, teach, develop and create solutions targeting social need and shaping a safe and