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effectively over extended distances. For this purpose, it is essential to develop a robust mapping algorithm, that allows for continuous, online map growth during exploration and mapping operations. The map
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(e.g. RNAi, CRISPR/Cas9, small-molecules). In this context, we also develop new computational tools for automated analysis and data visualization. These include algorithms and software applications
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with antenna array signal processing techniques Sound understanding of optimization methods and algorithms Proficiency in Python programming Proven publication record in top-tier international journals
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and AI algorithms Solid programming skills in Python and familiarity with machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch) Experience working with geospatial data (e.g., geopandas
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Isaac Sim, ensuring realistic physics for hybrid locomotion. You will develop and train RL algorithms for hybrid locomotion tasks, including transitioning between locomotion modes and balancing on uneven
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algorithms for microscopy image analysis problems (primarily 2D timelapse data), which are driven by real applications in life science research Develop solutions to integrate large foundation models
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Conduct comparative benchmarking and performance analysis against state-of-the-art studies Perform numerical modeling and validation of brain-inspired and neuromorphic algorithms Design, set up, and operate
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robotics Goal-driven agentic AI Autonomous medical imaging Design of AI-enhanced medical devices Machine learning models and algorithms for medical signal processing Embedded AI Privacy-aware AI Foundations
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technicians Image analysis using AI-segmentation algorithms Histological correlation of PET results and immunohistochemistry for tissues transduced by the vector Experimental design, realization, and analysis
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molecular biology techniques as well as in algorithms, statistics and artificial intelligence for molecular genetics. Importantly, mastery of the experimental and theoretical aspects shall equip doctoral