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photonics. Over the years, SPMS has attracted talented individuals from around the world and Singapore to join as scientific leaders and researchers. Key Responsibilities: To develop and setup the technique
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an emphasis on technology, data science and the humanities. We are looking for a Research Fellow to develop a chat agent for diabetic patients under Professor Andy Khong. The role will focus on developing LLM
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in the 2025 QS World University Rankings by Subjects. We are hiring a Research Fellow in Signal Processing and Machine Learning to develop signal processing and machine learning algorithms and methods
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out and oversee research projects in multimodal, generative, and embodied AI. The role will focus on designing, developing, analyzing, and evaluating large AI models to push the current boundaries. Key
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technologies (lipidomics, proteomics), cell biology, molecular biology and bioinformatics to clarify the mechanisms of key molecular interactions, and support the development of early diagnostic and intervention
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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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on developing the low-dimensional nanophotonics, focusing on the near-field, nonlinear and quantum optical properties of emerging low-dimensional materials. Key Responsibilities: The Research Fellow will work
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focus on translational Research, Development & Deployment which focus on specific area of the energy value chain, and a number of Living labs and Testbeds which facilitate large scale technology
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in the 2025 QS World University Rankings by Subjects. We are hiring a Research Fellow in Signal Processing and Machine Learning to develop signal processing and machine learning algorithms and methods
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, stability). Engineer antibodies for enhanced function (Fc modifications, bispecific formats, humanization). Evaluate therapeutic efficacy in cell-based assays and murine tumor models. Develop the workflow