31 affective-computing-"https:" "https:" "https:" "UCL" Fellowship positions at SINGAPORE INSTITUTE OF TECHNOLOGY (SIT) in United Kingdom
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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that are relevant to industry demands while working on research projects in SIT. The researcher will be part of the team of the CFI Project (https://www.pub.gov.sg/-/media/PUB/Resources/Press-Releases/2024/06/Annex
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, accumulated deformations, and their impact on structural performance, particularly for compression members. Develop data-driven reusability assessment platforms integrating NDT data, machine learning models
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that are relevant to industry demands while working on research projects in SIT. The researcher will be part of the team of the MCCS NATURE Project (https://www.nparks.gov.sg/Cuge/Programmes-Schemes/Research
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contribute to the advancement of coastal engineering and oceanography. Impact Assessment: Evaluating the potential impacts of storm surges on coastal regions, including flood risk assessments and vulnerability
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. Sustainability & Compliance: Assess environmental impact of materials; maintain lab safety and regulatory compliance. Required and Preferred Qualifications Bachelor's in Materials Science/Engineering or related
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the project requirements. Job Requirements: Competence in working with languages such as C along with AI applications as well as Python-based coding . Have a degree in Computer Science/Computer Engineering
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. Job Requirements: Competence in working with languages such as C along with Python-based coding and AI development. Have a degree in Computer Science/Computer Engineering. Possessing a Master’s or PhD
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offloading for public safety services. The successful candidate will be responsible for the end-to-end investigation of novel edge-assisted computation offloading strategies that leverages edge intelligence