59 evolution-"https:"-"https:"-"https:"-"https:"-"https:"-"U.S"-"U.S" Fellowship positions at Nanyang Technological University
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on carrying out research according to the proposed milestones. Key Responsibilities: The Research Fellow (RF) will work on a project to conduct the research on development of Self-Healing Ductile Cementitious
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of faculty, students and alumni who are shaping the future of AI, Data Science and Computing. We are seeking to hire a Research Fellow to support research and development in Generative AI, Statistical machine
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. Contribute to digital twin methodologies and predictive modelling. Execute experiments and deployments in laboratory and field environments. Publish scientific outputs and participate in grant development
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-disciplinary team and external collaborators for drug discovery and development Provide support in grant administration/management Job requirements: At least PhD degree in Chemistry, Biology, Biophysics
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development and implementation of arts-based programmes and to optimise the benefits from engaging in artistic experiences. The full project comprises four phases and involves eight sub-studies. It aims
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(Singapore), Nanyang Technological University and National University of Singapore. Hosted by NTU, IDMxS is focused on development of core science to drive a paradigm shift in molecular detection and analysis
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assessments, and attend regular lab meetings. Contribute to the overall development of competitive T-cell immunology translational research. Job Requirements: Ideal candidate for Senior/Research Fellow should
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(Singapore), Nanyang Technological University and National University of Singapore. Hosted by NTU, IDMxS is focused on development of core science to drive a paradigm shift in molecular detection and analysis
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on a project to conduct experimental research on the development of novel quantum photonic devices. The roles of this position include: Key Responsibilities: Design, fabrication, and characterization
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Responsibilities: Conduct programming and software development for graph data management. Design and implement machine learning models for optimizing graph data management. Conduct experiments and evaluations