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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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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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PhD Scholarship Help shape the future of solar energy. This iPhD project will develop a new technical framework for testing printed solar technologies—an emerging class of ultra-lightweight
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algorithms, and some knowledge of data science and machine learning (through coursework, self-learning, or personal projects). The selected student will work with Ph.D. and master's students to help develop
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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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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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conduct cutting-edge research on the interplay of theoretical computer science, mathematics, and quantum mechanics. Particular topics include classical and quantum aspects of: Sublinear algorithms and
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working with AI/ML experts for optimization algorithm development and associated experts for integration into the experimental workflow. You will work with a team that possesses focused skill sets (subject
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after deployment, leveraging recent advances in physical reservoir computing, contrastive learning, and biological decision-making paradigms. You will: - Develop and apply decentralized learning
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Engineering Laboratory (HRE Lab), providing the candidate with access to advanced experimental infrastructure and opportunities to contribute to the further development of the laboratory’s research and