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integrated sensor arrays. The project combines several different concepts: Progress in understanding insect neurobiology that provides proven circuit designs to solve significant problems such as autonomous
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of biotechnology and sensor devices. Finally, the synthetic systems we are developing can be used to mimic biological processes, such as transport of proteins through the membrane surrounding the cell nucleus. By
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comprehensive analysis of complex imaging mass spectrometry datasets (e.g., MALDI-MSI, DESI-MSI) using established computational frameworks Develop and implement novel algorithms and visual analytics for spatial
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optimization, AI, power electronics with good publication record· Good at coding in python with different DRL algorithms training, or good at digital platform development will be a preference Knowledge of
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writing scientific papers and communicating our research advances in conferences. Methods: programming a humanoid platform using ROS2 packages, solve SLAM, use imitation learning algorithms to learn pick
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of insects for more than a decade, both in terms of engineering field deployable sensors and also in terms of fundamental understanding of light interaction with free flying insects. We now aim to push
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-series modeling (EEG, video, sensor data) and chemical/structural data representation (e.g. graphs, SMILES strings, molecular embeddings). Familiarity with multimodal representation learning and
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analysis of complex, longitudinal, and high-dimensional data (e.g., immunometabolic profiles, clinical data, biomarkers). Development and application of predictive models and algorithms for diagnostics
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through interaction with their surrounding environment. Embodied AI requires tools, algorithms, and techniques to cope with real-world challenges including but not limited to uncertainty, physical
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setting. In this environment, our research group focuses on combining novel genome engineering tools (e.g., CRISPR-based) and computational algorithms to enable regenerative cell therapies. Now, we are