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supervising research staff, postdocs, students, and interns in relevant fields Experienced in cross-disciplinary research initiatives and collaboration Application: Please click the apply button and submit
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sampling-based and reinforcement learning-based motion planning algorithms for multiple robotic arms in automotive manufacturing, including testing, performance evaluation in both simulation and actual
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semiconductor design automation and fostering leadership in next-generation microelectronics research. Key Responsibilities: Lead and conduct research in applying AI and ML algorithms for signal integrity (SI
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of the designed algorithms and systems. Help with research presentation works such as high-quality paper writing. Job Requirements: Preferably PhD’s degree in Computer Engineering, Computer Science, Electronics
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Responsibilities: Conduct research on differential privacy algorithms with applications in computational processes. Develop innovative ideas to enhance existing algorithms and frameworks. Collaborate on applying
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. Our group develops machine learning algorithms to automatically generate discoveries from large-scale brain imaging data. We aim to uncover fundamental principles of healthy brain development
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, Effects, and Criticality Analysis (FMECA), functional FMECA, advanced sensing techniques, sensor and operational data fusion, data analytics, and machine learning algorithms for condition monitoring, fault
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administration experience, cloud and distributed computing. • Minimum of 5 years of experience in IT Operations, Infrastructure Management, or System Administration. • Experience managing servers, networks
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softwares and algorithms. Excellent publication track records. Good understanding of nonlinear and quantum optics. Strong knowledge of optical physics, while experimental experience would be preferred
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Cybersecurity, including decentralised/distributed trusted systems; biometrics; computer forensics; data, media content and related applications security and privacy; software and system security; information