80 distributed-systems-phd Fellowship positions at SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
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7 Apr 2026 Job Information Organisation/Company SINGAPORE INSTITUTE OF TECHNOLOGY (SIT) Research Field Engineering Researcher Profile First Stage Researcher (R1) Application Deadline 6 May 2026 - 00
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(Lua/Java), agent behavior modeling, event handling, and API-based integration with external AI systems. Experience with distributed systems, reinforcement learning, or simulation environments (e.g
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Master’s or PhD degree in relevant areas will be advantageous. Familiarity with the following areas is advantageous: Participation in Kaggle competitions, showcasing practical problem-solving and model
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that are relevant to industry demands while working on research projects in SIT. The primary responsibility of this role is to support and contribute to an industry innovation research project. The Research Engineer
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14 Mar 2026 Job Information Organisation/Company SINGAPORE INSTITUTE OF TECHNOLOGY (SIT) Research Field Engineering Engineering Chemistry Engineering Researcher Profile First Stage Researcher (R1
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Job Requirement Have relevant competence in the areas of Deep Learning/Computer Vision. The experience in diffusion models is a plus. Have a PhD degree in computer science/engineering or related
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7 Mar 2026 Job Information Organisation/Company SINGAPORE INSTITUTE OF TECHNOLOGY (SIT) Research Field Engineering Researcher Profile First Stage Researcher (R1) Application Deadline 5 Apr 2026 - 00
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deployment. Our research staff are equipped with industry-relevant skills through hands-on work on operational research platforms and systems. The Future Ship and System Design (FSSD) programme aims to develop
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external AI systems. Experience with distributed systems, reinforcement learning, or simulation environments (e.g., Unity3D, OpenAI Gym, WebGL) is advantageous. Experience in developing and deploying cloud
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(Lua/Java), agent behavior modeling, event handling, and API-based integration with external AI systems. Experience with distributed systems, reinforcement learning, or simulation environments (e.g