52 data-"https:"-"https:"-"https:"-"https:"-"Robert-Gordon-University" positions at SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
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cutting-edge computer vision technology. Working closely with the Principal Investigator, Co-PI, and interdisciplinary research team, RE will develop and implement deep learning algorithms to analyze trap
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cluster moulds electronic and computer engineers, computer scientists, AI engineers, interactive media and game development experts, software engineers, and information security specialists. We invite
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that are relevant to industry demands while working on research projects in SIT. This project focuses on federated causal inference in heterogeneous data environments, addressing the challenge of enabling trustworthy
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18 Nov 2025 Job Information Organisation/Company SINGAPORE INSTITUTE OF TECHNOLOGY (SIT) Research Field Engineering Computer science Researcher Profile Recognised Researcher (R2) First Stage
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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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carrying out tasks independently Where to apply Website https://www.timeshighereducation.com/unijobs/listing/401534/research-engineer-f… Requirements Additional Information STATUS: EXPIRED X (formerly
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into viable partnerships across areas such as Generative AI, Large Language Models, Computer Vision, Digital Twins, and Multimodal AI. Success in this role requires strong commercial instincts, the ability
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team members to ensure all project deliverables are met. Accumulate data from Co-PIs for quarterly, annual, or final progress reports• Schedule meetings with co-PIs, collaborators on-site or off-site
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Validation: Oversee the AM process and testing of 3DP ship hull and connector system. Data Collection and Analysis: Gather testing data during for design optimisation. Reporting and Documentation: Prepare
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, advanced sensing techniques, sensor and operational data fusion, data analytics, and machine learning algorithms for condition monitoring, fault diagnosis, and early fault prediction in electric vessels