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. Requirements: PhD degree in statistics or a related field from a reputable university. Solid knowledge in hypothesis testing and high-dimensional analysis. Strong proficiency in the R programming language
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with a team, have an investigative nature and attention to detail; have knowledge of computer applications (such as SPSS and MS Office, PowerPoint); and have good communication skills with patients and
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. Maintain clear records of sample preparation protocols, imaging parameters, and results. Share knowledge and provide guidance on sample preparation and imaging workflows as needed. Collaborate with
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operation of the system and applications. • Strong knowledge of power electronics, drives, and control is highly preferred. Experience with hardware testing and real-time simulation will be advantageous
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. • Assist in supervising graduate students where applicable. • Contribute to knowledge dissemination through conferences, workshops, and seminars. Qualifications • A doctoral certificate (PhD or
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strongly advantageous. Working knowledge of sensor fusion, time-series analysis, or edge-computing in environmental monitoring applications. Working knowledge of sensor calibration and data quality control
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project: “Climate Transformation Program (CTP): Cross Cutting Theme 1 – Sustainable Societies” funded by the MOE Tier 3C Grant. CTP aims to develop, inspire, and accelerate knowledge-based solutions and
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oriented architectures and NoC (Network-on-Chip) enhancements with a focus on long-term security, integrated hardware security functions, hardware root-of-trusts (RoT) and cryptographic agility Knowledge and
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and NoC (Network-on-Chip) enhancements with a focus on long-term security, integrated hardware security functions, hardware root-of-trusts (RoT) and cryptographic agility Knowledge and/or experience in
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robotics systems. • Strong mathematical background with solid knowledge in numerical optimization theory. Familiarity with semidefinite programming and its convex relaxation techniques is highly preferred