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plant resistance genes using effectoromics approaches in plant–microbe interactions. This position focuses primarily on experimental biology, including molecular, genetic, and cell biology approaches
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Associate (Master’s level) Master’s degree in Molecular Plant-Microbe Interactions, Biotechnology, Molecular Genetics, Functional genomics, or a related field Experience with plant molecular biology
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and navigation algorithms for robot in complex environments. Key Responsibilities: Responsible for development of robust and reliable sensor fusion algorithms for localization and navigation algorithms
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) to develop accelerated AI, machine learning, and robotics algorithms with a strong focus on computational efficiency, memory reduction, and energy-aware deployment. The role targets foundation models
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exploration and relevant disciplinaries Key Responsibilities: Develop novel imaging algorithms and validate them through synthetic experiments Extend these methods to real-world experiments to address practical
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on computer vision. The role will focus on developing, designing, and implementing novel algorithms and models to address emerging problems in computer vision, such as Multimodal Large Language Models and
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, and learning capabilities Develop and optimize data-driven algorithms for anomaly detection and incident response Implement scalable, modular, and containerized solutions compatible with platforms
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effectiveness of battery recycling workflows, supporting experimental and simulation studies across the battery lifecycle, and implementing algorithms for process monitoring and optimization so that recycling
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algorithms with surgical robotics. The RA will design and implement cutting-edge algorithms, and also be actively involved in the development AI tools tailored for different medical domains. These are efforts
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deep learning algorithms to enable robotic arms to perform complex tasks guided by natural language instructions. Experiment with and deploy vision-language-action models on robotic platforms