1,365 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"MPG" positions in Singapore
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AI/ML models for predicting materials properties using data-driven approaches, including the treatment of disordered inorganic materials. Develop codes as necessary to assist existing and new code
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., Human Biomedical Research Act, Medicines Act, Personal Data Protection Act, Penal Code, Health Products Act, etc, and their related Regulations) and to NUS’ policies and guidelines (e.g., DMP, RDMP, etc
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spectroscopy. Candidate will also have the opportunity to learn MR data processing and programming if keen. Main Duties and Responsibilities Perform MR imaging on a range of body parts and MR techniques
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boundaries of AM material innovation and supports NTU’s commitment to sustainable and impactful technological development. Key Responsibilities: Conduct data acquisition campaigns, collecting synchronized
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Description To augment OAR’s Data & Systems (D&S) team and take on the management of the Alumni CRM (Blackbaud CRM) and Event System (Gevme) allowing existing D&S staff to undertake the migration of the Alumni
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, and full-stack development, supporting the deployment of intelligent, data-driven solutions that are reliable, efficient, and user-focused. Key Responsibilities: Design, develop, and maintain scalable
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processes for postgraduate students: a) Verify and analyse applicant information for accuracy, relevance, and completeness to ensure informed decision-making. b) Database management–maintain data
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. Administer the College-level undergraduate awards, grants, and bursaries. Compile Student Experience Survey and Graduate Employment Survey data. Provide operational support for the planning and execution
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and testing Cloud Native & Serverless Computing Containerization & Orchestration Agile SDLC, DevOps and AI automation tools Architecting Big Data systems(NoSQL, data lakes, data warehouses) Real time
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and data pipelines to enable real-time data acquisition and closed-loop control. Collaborate with AI researchers to implement machine learning models for adaptive experimental design and autonomous