27 expert-system "https:" Fellowship research jobs at SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
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-destructive testing (NDT) techniques for structural materials is desirable. Experience with structural modelling and analysis tools (e.g., finite element modelling, structural simulation) is desirable. Good
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learning and development Proficient in technical writing and presentation Possess strong analytical and critical thinking skills Show strong initiative and take ownership of work Where to apply Website https
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or authorisation to design and operate high-power or high-voltage electrical systems Minimum 2 years of relevant experience Key Competencies Good knowledge in electrical equipment and power system design. Good
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7 Apr 2026 Job Information Organisation/Company SINGAPORE INSTITUTE OF TECHNOLOGY (SIT) Research Field Computer science Engineering Researcher Profile Recognised Researcher (R2) First Stage
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18 Apr 2026 Job Information Organisation/Company SINGAPORE INSTITUTE OF TECHNOLOGY (SIT) Research Field Biological sciences Researcher Profile Recognised Researcher (R2) First Stage Researcher (R1
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18 Apr 2026 Job Information Organisation/Company SINGAPORE INSTITUTE OF TECHNOLOGY (SIT) Research Field Engineering Researcher Profile First Stage Researcher (R1) Application Deadline 17 May 2026
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18 Apr 2026 Job Information Organisation/Company SINGAPORE INSTITUTE OF TECHNOLOGY (SIT) Research Field Engineering Engineering Researcher Profile First Stage Researcher (R1) Application Deadline 17
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10 Apr 2026 Job Information Organisation/Company SINGAPORE INSTITUTE OF TECHNOLOGY (SIT) Research Field Agricultural sciences Researcher Profile First Stage Researcher (R1) Application Deadline 9
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28 Mar 2026 Job Information Organisation/Company SINGAPORE INSTITUTE OF TECHNOLOGY (SIT) Research Field Computer science Engineering Researcher Profile First Stage Researcher (R1) Application
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(Kubernetes), serverless computing, and REST API development. Proficient in Python, with basic experience in machine learning or computer vision libraries; familiarity with Vision-Language Models (e.g., CLIP