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The College of Computing & Data Science (CCDS) invites applications for the position of Research Fellow. Key Responsibilities: Responsible for performing quality assessment for 3D digital asset
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for asymmetric catalysis and C-H functionalization. Key Responsibilities: Conduct routine lab research and data analysis in organic chemistry and organometallic chemistry. Assist in instrument installation and
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conferences/journals. Involve in the mentoring of PhD/Masters/FYP students Job Requirements: Possess a PhD degree in Computer Science or Electrical and Computer Engineering Experience in point cloud analytics
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Research Fellow (Process Control/Control Science & Engineering/Applied Mathematics/Machine Learning)
Requirements: Obtained a PhD degree (or will be awarded PhD degree shortly) in Process Control, Control Science And Engineering, Applied Mathematics, Machine Learning or related fields. An excellent track record
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. Job Requirements: PhD in Mechanical Engineering, Aerospace Engineering, or Robotics. Experienced CAD user (SolidWorks or Fusion 360). Evidence (e.g. portfolio) of prototype development from concept
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of the project support. Candidates should have a PhD degree in a quantitative field, such as data science, computational biology, mathematics, computer science, (bio)statistics, or related field. Research
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The School of Civil and Environmental Engineering (CEE) is inviting applications for the position of Research Fellow. The Research Fellow will support the research for the project involving the use
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The School of Civil and Environmental Engineering (CEE) is inviting applications for the position of Research Fellow. The Research Fellow will support the research for the project involving the use
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emerging technologies. Sustainability is a top priority for SC3DP, which offers material development and control services that combine artificial intelligence, big data, and other digital tools for process
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: Possess a PhD degree in computer science, electronic engineering, applied mathematics, perception sciences, etc. Background knowledge in signal/data compression, and data-driven and machine learning