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competitive ERC. The project focuses on the development of a first-principles, machine-learning-accelerated computational framework for modelling polymorphism, anharmonicity, and electron–phonon interactions in
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para Ciência e Tecnologia; - PhD in Electrical Engineering, Computer Science, or equivalent scientific areas - Excellent academic and practical background in machine learning, deep learning, natural
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condition: work experience related to modular curves, Galois representations, modular forms or machine learning for number theory. The supporting evidence should include a list of published papers
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students. Assist in grant proposal applications. Requirements: PhD in Mechanical Engineering, Machine Learning, Artificial Intelligence, Computational Mechanics, Material Science, Industrial Engineering, or
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technical specifications. Knowledge, Skills, and Abilities: Advanced applied statistics skills, such as distributions, statistical testing, regression, etc. Professional experience developing machine learning
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2,900 work in administration and organisation. We are looking for a/an University assistant predoctoral/PhD Candidate Optical Quantum Computing and Machine Learning 51 Faculty of Physics Startdate
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want to hear from you! Your Job: Work on a wide range of computer vision and machine learning methods and applications focusing on the aspects outlined above, inspired by the needs of societally relevant
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the internal peer group. BNL policy requires that after obtaining a PhD, eligible candidates for research associate appointments may not exceed a combined total of 5 years of relevant work experience as a post
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your work at international conferences. Supervise motivated PhD candidates and contribute to the research community. Shape the next generation of AI talent (50%) Teach engaging courses in AI, machine
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group. BNL policy requires that after obtaining a PhD, eligible candidates for research associate appointments may not exceed a combined total of 5 years of relevant work experience as a post-doc and/or