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applications for a Postdoctoral Fellow to join an international research team on the Marsden Fund project Scalable Bayesian Algorithms for Multi-Physics Inverse Problems with High-Level Representations
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Responsibilities The incoming postdoctoral researcher will lead or contribute to key research activities within the LU-PCG, advancing control theory, machine learning algorithms, and integrated simulation workflows
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will have a strong background in wireless communication, signal processing, and machine learning. They should also possess the skills necessary to develop complex models, algorithms, and simulations
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, big data frameworks, bioinformatics, data analysis, data science, discrete and machine learning algorithms, distributed, intelligent, and interactive systems, networks, security, and software and
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for data processing and distributed workloads. Optimize PostgreSQL performance, backups, and reliability. Improve monitoring, logging, deployment, and production reliability. Contribute to backend services
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neuroimaging methods to better detect disrupted function following neonatal brain injury, and identify new more energy efficient learning algorithms that could reduce the economic and environmental cost of AI
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optimization algorithms is highly desirable Excellent programming skills in Python, C++, Java, Julia, or other relevant languages Knowledge of maritime decarbonization and alternative fuels is a plus A good
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offers a friendly and international work environment Learn more about CQT at https://www.cqt.sg/ The research fellow will work closely with PI Patrick Rebentrost on developing novel quantum algorithms
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practices Contribute as a co-author to interdisciplinary peer-reviewed manuscripts, with primary responsibility, as appropriate, for computational, algorithmic, and data-methodology sections Contribute
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statistical methods, computational models and/ or machine learning algorithms to analyse environmental and infectious disease data; - Collaborate with multidisciplinary and international teams of researchers