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multi-omics data integration and the project will provide opportunities to learn, develop, and apply machine learning and deep learning methods on genomics data. Requirements: excellent university and PhD
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. The platform enables automated behavioral analysis and supports researchers with valuable insights. What you will do Develop and maintain machine learning inference pipelines using Python and Docker Support
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Interactions in a Changing World” is an interdisciplinary research initiative of geoscientists, biologists, and computer scientists at the Universities of Tübingen and Hohenheim and the Senckenberg Institution
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essential. Good programming skills in at least one programming language (e.g., Python). Experience with machine learning, LLMs, or HCI/user study methodologies will be a plus. Strong interest in acquiring and
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presentation using common computer programs Ideally, strong communication skills in both German and English You are enthusiastic about learning new practical skills, approach unfamiliar topics with curiosity and
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). Knowledge of Docker and machine learning is considered a plus. Knowledge of standard bioinformatics tools for analyzing and interpreting Next Generation Sequencing data. Excellent oral and written
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team and actively participate in the DIPONI project (“Digital Transformation in Polymer Processing: Interoperability and Machine Learning Solutions for Process Optimization and Sustainability
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the research area of adversarial robustness in LLMs as a Doctoral candidate / PhD Student (f/m/d) At the chair of Data Analytics and Machine Learning at the Technical University of Munich (TUM), a full position
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the fields of Quantum Machine Learning, Quantum Simulation, and Quantum Optimization. These solutions are made available to the German economy as digital services, while targeted knowledge transfer ensures
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macromolecular dynamics with statistical mechanics, molecular simulation at different resolutions, machine learning, and experimental data. Our group works on the definition and implementation of strategies