64 evolution-"https:"-"https:"-"https:"-"UCL"-"UCL" Fellowship positions at Nanyang Technological University
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Hyundai-NTU-A*STAR Corp Lab serves to drive research development and industry adoption of 3D Printing technologies through collaborative projects with HMGICS, and with schools and research centres
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Hyundai-NTU-A*STAR Corp Lab serves to drive research development and industry adoption of additive manufacturing technology through collaborative projects with leading industry partners, and with
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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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molecular mechanisms of fish immunity, conduct immune and metabolomics analyses, and support the development of oral vaccine delivery systems to promote sustainable aquaculture. Key Responsibilities: Lead
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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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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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-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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We are looking for a Research Fellow to conduct the research for the project entitled “Manual Assembly Job Quality Inspection”. The role will focus on research and development of AI algorithms
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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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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