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the industry to lead and/or conduct innovative research on, but not limited to evolutionary computing, job scheduling, transfer optimization, transfer learning, reinforcement learning, large-scale
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. Develop and enhance advanced optimization algorithms for the Energy Management System (EMS), addressing energy dispatch, storage control, load scheduling, and strategies for market participation. Architect
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environments. Develop and refine advanced optimization algorithms for the Energy Management System (EMS), including energy dispatch, energy storage control, load scheduling, and market participation strategies
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technologies. Key Responsibilities: Design and manufacture bio-inspired soft gripper system with optimal structure. Design and develop tactile sensing mechanism on the developed robotic systems. Create embodied
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history, and compliance Collaborate with Data/IT teams for CRM integration and automation improvements Analytics & Optimization Analyse lead funnel performance Monitor call-to-conversion ratios and lead
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application like drug delivery. Key Responsibilities: The Research Fellow will work on a cross-disciplinary project at the intersection of mechanics, acoustics, design optimization, and advanced manufacturing
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system performance in physiologically relevant settings. Explore and implement AI/ML tools for system optimization, data-driven control, or high-throughput analysis. Contribute to publications, IP filings
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algorithms, models, and techniques. - Perform rigorous benchmarking and evaluation of the developed models. - Optimize algorithms for efficiency and scalability. Collaboration & Mentorship - Work closely with
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, particularly in Southeast Asia. Comprehensive understanding of the various mainstream and digital platforms and the know-how to integrate content and platforms for optimal audience engagement. Good knowledge and
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compatibility analysis of materials for different components Mechanical characteristics evaluation and optimization Support mechanical and chemistry relevant qualification and failures analysis Drive specific