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biomarkers, and electronic health records) and developing computational models. Establishes frameworks for data modernization, integrating metadata and varied datasets to create databases suitable for cross
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aspects of computational modelling, brain-computer interface technologies as well as within NUS focusing on design and application from the lens of landscape architecture. Key Responsibilities: Assist
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planning. b) Have knowledge of statistical computing, data science, data modelling, or data visualisation languages and software (e.g., PowerBI, Python, R, SAS, SPSS, SQL, Tableau, etc.) c) Have experience
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or microworlds, conduct laboratory studies, and construct computational cognitive models including paradigms in Cognitive Science (Instance-Based Learning models) or AI (Reinforcement Learning). The fellow will
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metapopulation and/or individual based models Knowledge of Bayesian methods, including Approximate Bayesian Computation Experience with big data analysis and HPC environments Knowledge of additional programming
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The Emerging nanoscience Research Institute (EnRI) focuses its research on advanced materials, computational modelling & simulation and development of small-scale testing and materials
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) at Duke-NUS Medical School is seeking a Research Fellow to support the ongoing “Future Health Technologies” (FHT1) research programme. FHT1 is dedicated to developing innovative, scalable digital solutions
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collection methods. You’re skilled in developing computational models and deep neural networks that reflect principles of human cognition and brain function. Your academic record includes high-quality peer
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’) with responsibility for the day-to-day project, budget and research activities. You will also undertake research including developing and fine-tuning large language models and topic modelling methods
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to the creation of knowledge by undertaking a specified range of activities within an established research programme and/or specific research project. We are looking for up to two Postdoctoral Researchers