363 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" uni jobs at National University of Singapore
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operational modelling and simulation, pricing & cost control to contribute to growth of the team resources. The ideal candidate is highly organized and proficient in using current data and machine learning
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of AI / deep learning / machine learning / statistics on spatial and single-cell omics (transcriptomics, proteomics, epigenomics, metabolomics, meta-transcriptomics, etc.) data. Independently carry out
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-related and miscellaneous duties as assigned by the Department when there are manpower requirements at the Design Lab to support the lab classes and train new users on the testing machines Qualifications
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or personal mentorship; capture feedback on knowledge sharing and technical problem-solving impact. Identify real-world AI projects that build software engineering depth and machine learning pipeline skills
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, machine learning, AI, computer vision, large language models, Agentic AI or human–computer interaction. Excellent oral and written communication skills. Resourceful and up-to-date with developments in
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, with demonstrated excellence in both methodological research and clinical application of artificial intelligence and machine learning (ML). The candidate will contribute to high-impact research
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safe working environment. Qualifications Polytechnic Diploma in an engineering field or other equivalent engineering qualification Experience in engineering work, lab operation Basic computer skills such
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Technologies (AICET) under one of the AICET’s projects. Current projects include: Codaveri – An auto-feedback programming system Coursemology - a gamified e-learning platform Softmark – An online grading too
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biomedical laboratory work; assist with experimental workflows as required Qualifications Diploma in Biotechnology, Biomedical Science, or a related field Basic computer proficiency (email, Microsoft Office
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efficiency by learning from and collaborating with other clinical trial networks. In the long term, the Network aims to support broader infectious disease studies by expanding geographically beyond its