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in data integration, model design, and large-scale training by combining multi-modal scientific data, knowledge graphs, physics-aware machine learning, and GPU/HPC computing to develop transparent and
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to a positive performance evaluation. Keywords: Atomic physics, Simulations, Rydberg Atoms, Many-body quantum physics, Quantum information theory, quantum computing, artificial intelligence, machine
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. About You You will have, or be close to completion of a PhD/DPhil in Statistics, Machine Learning, Data Science, or a related quantitative discipline. You will demonstrate strong specialist knowledge in
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and have synergiccollaborationeffects. Weexpect a motivatedearlycareer researcher with stronginterest and experience with GIS/earth observation/climateprojection data as well as machine learning models
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Lab at Princeton University aims to recruit a postdoctoral fellow or more senior research position to work on projects related to the development of AI/machine learning approaches for chemical and
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DEI work here https://group.springernature.com/gp/group/taking-responsibility/diversity-equity-inclusion For more information about career opportunities in Springer Nature please visit https
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sociology. Strong quantitative skills and experience with large-scale data analysis required. Computer Science/HCI: PhD in Computer Science, Human-Computer Interaction, Information Science, or related
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mutations, etc.), analysis and integration of mass-spectrometry proteomics datasets, and artificial intelligence/machine learning (AI/ML) and systems-biology-focused efforts (i.e. large genomics and
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psychology for which there is appropriate supervision expertise within the school. More information on potential PhD projects can be found here: https://www.plymouth.ac.uk/schools/psychology/phd-studentships
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of the Alhambra and the Generalife. Project 2 — Machine learning for energetic-particle transport in thunderstorms This project explores machine-learning (ML) techniques to accelerate the numerical simula- tion