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) and economics (or related fields). Applicants must have experience in one or more of the topics: Model-predictive control Numerical optimization Econometrics Virtual power plants Power systems and/or
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. Material Optimization: Use optimization algorithms to design FGMs that meet demanding performance criteria like fatigue resistance and durability. Systems Integration: Apply a systems engineering approach to
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metabolomics core and research facility in Singapore, actively contributing to numerous projects aimed at uncovering disease mechanisms through advanced metabolomics profiling. We are seeking a Research Fellow
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to implement and optimize AI/ML models for biomedical datasets. Preferred Knowledge, Skills and Abilities Mathematical Modeling: Strong foundation in numerical modeling, graph theory, and statistics. Algorithm
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processes. As theoretical understanding of such nonclassical states has advanced over the past few years, numerous experiments will be required to verify and further optimize them for potential applications
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performance, safety, and scalability. The project may involve both experimental investigations and numerical simulations, depending on the candidate’s background and the evolving needs of the research
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interest in connecting theory with experiments, demonstrated skills in analytical and numerical computation, and a broad expertise in fields such as atomic physics, quantum optics, quantum optimal control
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among climate models and representative concentration pathways (e.g. emissions scenarios). Objective 3: Identify site-specific optimal vegetation treatments for minimizing extreme fire behavior
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the years by numerous scientists and technical staff working to protect both military personnel and civilians from the threat of infectious diseases. The Institute participates in support of emerging disease
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in the following areas: Deep Learning, Scientific Machine Learning, Stochastjc Gradiant Descent Method, and Numerical PDE’s - Advised by Dr. Yanzhao Cao Probabilistic Graph Theory (Network Traversal