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hybrid quantum-classical or quantum-AI approaches. Projecting short- to medium-term advances in hardware and algorithmic development for practical deployment. Salary Range: €47,273 - €53,925 per annum
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multidisciplinary fields, participation in academic conferences, experience from scientific publishing and other personal and professional development. The project will be carried out at Luleå University
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quantum matter and quantum computation. Our research includes (1) AI for Quantum: developing advanced AI algorithms grounded in physical principles and machine learning theory to tackle key challenges in
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international collaborators. The group's interests cover a wide range of areas including extremal and probabilistic combinatorics, combinatorial optimization, graph theory, game theory, algorithmics and geometry
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and porting of scalable science applications and algorithms for OLCF and other leadership computers. Debugging and tuning applications for high performance. Developing performance models of existing
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Researcher position. The selected candidate will work on research and development for testing, analysis, and integration of AI and machine learning (ML) algorithms in new simulation and training architectures
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. The tasks include battery cell characterization and modelling based on laboratory tests, and development of algorithms for estimating the charge level, health, and power capability which includes robustness
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, including prediabetes, type 1 and 2 diabetes, and non-alcoholic fatty liver disease (NAFLD). Their research informs artificial pancreas algorithms and contributes to drug development targeting hepatic
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 1 month ago
, scientific computation, scientific software and algorithm development, and data analysis; demonstrated ability to conduct original, high-quality research in computational fluid dynamics and/or computational
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on developing deep learning methods for the reconstruction and physical analysis of ATLAS experiment data. The selected candidate will develop innovative analysis methods for the reconstruction and physical