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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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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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https://www.cvc.uab.es/blog/2025/11/21/phd-position-on-continual-learning-of-fo… Work Location(s) Number of offers available1Company/InstituteComputer Vision CenterCountrySpainState
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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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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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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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application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is inherently spatio-temporal, i.e. physical processes
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CeMM - Research Center for Molecular Medicine of the Austrian Academy of Sciences | Austria | 25 days ago
the Medical University of Vienna, the Technical University of Vienna and University of Vienna, the AITHYRA and CeMM PhD programs for both life scientists and computational scientists/machine learning experts
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profiling, and other cutting-edge, high-dimensional tissue analysis approaches to evaluate pancreatic cancer pathology using human tissue specimens Assemble analysis pipelines using machine learning