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on novel agent architectures, including tool-use methodologies, advanced planning algorithms, and multi-agent collaboration for simulation-based optimization. Innovate & Conceptualize: Design and
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Responsibilities: Conduct individual research within the designed project: process data, develop research methods, build and evaluate computer vision and machine learning algorithms empirically. Author research
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learning algorithms (Deep learning, Reinforcement learning, etc.); Proficiency in written and spoken English - essential for data analysis and communication with stakeholders Excellent oral communication
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data processing, ship hydrodynamics, ship performance analysis, machine learning algorithms; Proficiency in written and spoken English - essential for data analysis and communication with stakeholders
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ICs. Development cycle including circuit design, simulation, modeling, layout, verification and measurements Design high power-efficiency RF power amplifiers Develop scripts and algorithms for analog IC
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aquaculture (e.g., behavioral analysis, growth prediction, digital twin, computer vision.) Develop, train, and validate advanced computational models and machine learning algorithms tailored to complex datasets
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objects and segmentation models for a robotic pick and place project. Develop data augmentation/data synthesis methods to address challenges from limited training data. Develop algorithms to annotate 2D
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” wherein messages including emotions are incorporated into the movements of collaborative robots. Key Responsibilities: Design, implement, and test real-time multi-objective motion planning algorithms
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cross-functionally with control engineers, hardware designers, and system integrators to integrate real-time control algorithms and maintain a robust test bench environment for prototype evaluation
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on business logic and application requirements. Design and implement AI algorithms for battery/energy storage systems to improve the prediction accuracy and decision-making capabilities of the digital twin