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and units within the university. Its primary goal is to streamline and optimize processes, enhance operational efficiency, and deliver high-quality services to support NTU's core mission of education
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, including traffic prediction, optimization, and safety enhancements. Key Responsibilities: Develop and implement machine learning models for air traffic prediction, flow management, and conflict detection
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Geospatial Laboratory. This pivotal role ensures seamless functionality, safety compliance, resource optimization, and fosters innovation through modernizing workflows and process enhancements. Collaborating
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multidisciplinary team driving transformative sensing technologies. Key Responsibilities: Develop and optimize fabrication processes for sensor arrays based on 2D materials (e.g., graphene, MoS₂), including flexible
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: Investigating novel optical materials and technologies Developing and optimizing optical system designs using simulation tools Characterizing and testing optical system performance Collaborate with cross
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efficient obstacle avoidance strategies to ensure collision-free navigation in dense settings. Implementing and validating algorithms in both virtual and real-world scenarios to optimize performance in indoor
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Responsibilities: Conduct research on the design and analysis of scalable machine learning systems using convex/nonconvex optimization and federated learning methods. Develop algorithms and prototypes
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. Responsibilities: IT Project Governance Oversee and optimize the IT project portfolio, ensuring alignment with organizational strategic goals. Define, track, and report on key performance indicators (KPIs) and
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serve as a strategic legal advisor, driving excellence in legal and compliance frameworks while fostering innovation, partnerships and optimization. This role requires a seasoned legal professional with
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writing/presentation Job Requirements PhD degree in an engineering field related to this project Experience in dynamic modeling, machine learning and optimization & controls Having basic knowledge in carbon