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computational materials science techniques (DFT, MD, machine learning force field modelling) with data-driven approaches. Work with team to design and implement high-throughput experimental workflows for rapid
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and refine algorithms and models for large-scale language processing tasks, with a focus on healthcare data Contribute to developing new models, techniques and methods for clinical machine learning
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and the analysis of large-scale assessment data: Methods and approaches to synthesize large data sets via meta-analyses (e.g., meta-analyses of large-scale assessment data, meta-analyses of meta
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-scale assessment data, meta-analyses of meta-analyses) Methods and approaches to cumulative, living, and community-augmented meta-analyses Methods and approaches to include machine learning and artificial
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training materials for research teams, focusing on data science and machine learning techniques in geoscience. Position description: PD [Research Fellow] [520112].pdf To learn more about this opportunity
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undergraduate programmes in Software Engineering, Computer Engineering, Computer Science, and Bioinformatics, as well as a number of combined degrees with other disciplines. Our research and teaching staff
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) The Centre for Quantum Technologies (CQT) in Singapore brings together physicists, computer scientists and engineers to do basic research on quantum physics and to build devices based on quantum phenomena
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& Development - Conduct original research in deep learning, related to uncertainty quantification for large models. - Explore cutting-edge advancements in AI and relate it to the main research objective
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Digital Twin for electric vehicle applications . The role will focus on utilizing novel machine learning models, large language models, and data science algorithms to develop battery models, optimization
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with strong background in Computer Vision and Machine Learning. Position Overview: In this position, you will investigate the existing solutions for assessing datasets and developing a novel tool relying