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The School of Physical and Mathematical Sciences (SPMS) at NTU Singapore hosts research and education activities in two divisions: Division of Mathematical Sciences (MAS) and Division of Physics and
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related areas. Develop new theoretical models, methodologies, and algorithms. Publish research outcomes in leading peer-reviewed journals and conferences. Prepare grant applications, technical reports, and
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learning based synthetic data generators that obtain both good utility and protection of privacy, through tailored model approximation, as well as new measures of privacy and fairness to be used
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. Knowledge of fluid mechanics, computational mechanics, mathematical modelling, numerical methods, or medical image analysis is considered an advantage. Experience with experimental fluid mechanics, laboratory
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of PhD submission. Strong scientific programming skills in Python. Knowledge of mathematical models of biological systems and numerical methods for differential equations. Experience developing and
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& optimization modelling, and data-driven assessment of compliance pathways, fuel transition, and strategic implications for shipping and maritime ecosystem. Key Responsibilities Conduct quantitative and scenario
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to interpret mathematically different classes of AI models, and which we believe can be used in manufacturing contexts. The outcome of this work will be a validated compilation of quantitative information
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with demonstrated ability to implement and optimize AI/ML models for biomedical datasets. Preferred Knowledge, Skills and Abilities Mathematical Modeling: Strong foundation in numerical modeling, graph
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. Strong background in the mathematical modeling of multiscale and multiphysics phenomena, including proven application of dimensional analysis, fractal analysis, and hybrid physics–AI approaches
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of placental function and reduce the risk of stillbirth. This post forms part of the internationally funded Wellcome Trust programme, which aims to develop new approaches to measure, model and predict pregnancy