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Field
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, you will focus on developing mathematical models and numerical algorithms that systematically integrate uncertainties into the design process of optical systems. The goal is to enable novel design
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, the ability to analyze the full dataset collected by the experiment will be severely limited. The L2IT is a leader in developing new track reconstruction algorithms using geometric deep learning methods
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exciting opportunity for you to join our team working on Scientific Machine Learning (SciML). The project focuses on developing scalable HPC algorithms and mixed-precision solvers to train neural models
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to trust. By contrast, symbolic approaches have reliability and explainability "built in", since they are based on logical reasoning. This motivates the development of neurosymbolic approaches as a way of
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worlds. You will design QEC codes suited to realistic hardware, develop the decoding algorithms that make them practical, and map the trade-offs between reliability, qubit overhead and decoding latency. A
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to an obtained doctoral degree. We have a vacancy for a PhD Candidate in Databases and Search group for developing efficient search engines at the Department of Computer Science. The position is funded by
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connections. The project will have theoretical and algorithmic developments, software developments, and industrial case studies. Duties of the position Complete the doctoral education until obtaining a
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of repeatedly solving wave equations. In the project, we will develop a new mathematical and computational framework that combines PDE-based modelling with ideas from data-driven reduced-order modelling. The aim
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Python and/or C++. Experience with scientific software development is an advantage. An interest in quantum algorithms and the motivation to contribute to one of the world’s emerging research areas. Strong
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expertise in artificial intelligence, computer vision, human-computer interaction, and psychology. Its technical core lies in developing robust and adaptive visual speech recognition models. Close