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Field
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the project leader in the research project - “Development of automated surface waviness detection and analysis from high-density point clouds”. They will be required to: (a) conduct advanced research on
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is highly preferred. • Systems: Experience running experiments on HPC clusters or cloud environments. • Documentation: Ability to use LaTeX and scientific writing tools for technical reporting
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electrical engineering, Computer Science, or any other relevant subject. Specific skillsets include programming skills such as C and Matlab, and experience with Amazon Cloud. Priority would be given
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-performance computing (HPC) clusters or cloud GPU instances. Analytical Rigor: Ability to design ablation studies to isolate the impact of individual loss components. Communication: Ability to clearly
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improvement of development infrastructure (e.g., CI/CD, Docker, cloud-based services). Carry out Risk Assessment, and ensure compliance with Work, Safety and Health Regulations. Coordinate procurement and
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, shape analysis, etc, which may involve CAD models, point cloud, meshes, neural implicit representation, Gaussian splatting, etc Help advise students and junior research staffs Contribute to technical
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regular meetings with the research group. Ph.D. in Electrical Engineering, Computer Engineering, Computer Science, or a related field. Proven experience working with wireless sensors, point cloud data
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/React, HTML/CSS) with D3.js or Plotly.js; Cloud backend (Firebase/Firestore) experience; Experience with gamification design and user experience (UX) principles; Experience with user testing and iterative
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across records. Develop a cloud-based verification platform for digital data collection and real-time analytics. Develop and apply non-destructive testing (NDT) methods and data-driven approaches
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cardiometabolic disease Track record of peer-reviewed publications relative to career stage Experience with multi-omic data integration Familiarity with HPC or cloud computing environments Monday through Firday