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degree or PhD in Computer Science, Electrical Engineering, Control Systems, or a closely related field. Experience in reachability analysis, formal verification/model checking, control theory, or related
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Documented expertise in developing and training machine learning models (ideally with a focus on LLM), high-performance computing, data management, and software architecture Strong Python programming skills
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epithelial cell biology, cellular metabolism and mitochondrial function. Experience in mouse models and ex vivo organoid culture is a prerequisite. The candidate should also have the ambition and commitment
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-XRF, Raman, FTIR in reflection mode) to enable multimodal data fusion and automated material characterization. • Apply and further develop machine-learning and statistical models (e.g. PCA, SAM
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-edge field of Human-Centered AI Technologies using advanced Generative AI and novel interaction technologies. Potential Ph.D. projects may focus on large language model (LLM) research. Ph.D
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Mathematics (analysis, numerics, modeling) or in a comparable program with a strong mathematical focus and knowledge in, for example, functional analysis as well as the theory and numerics of PDEs. Strong
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adaptive robotic strategies. The work will involve the integration of: Advanced motion planning and control algorithms Multi-modal perception techniques (e.g., vision, tactile, force) Machine learning models
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Master's degree in Mathematics, Statistics, Operations Research, Industrial Engineering, Computer Science, Data Science or a related field Strong mathematical and analytical skills for model formulation
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generation of stem-cell derived models, these platforms open new avenues to systematically explore tissue self-organization and disease mechanisms. The group of Prof. Bausch is establishing an automated cell
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involve the integration of: Advanced motion planning and control algorithms Multi-modal perception techniques (e.g., vision, tactile, force) Machine learning models for physical behavior prediction and