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Doctoral student in Applied Mathematics with a focus on Computer Vision and Spatial AI (PA2026/1165)
, you will be trained to think critically and analytically, to solve problems independently using the right methods, and to develop an awareness of research ethics. In addition, you will have the
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Sapere Aude – dare to know – is our motto. Our students and employees develop important knowledge that enrich both the individual and the community. Our academic environment is characterised by
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), and the European Innovation Council (EIC). Project description Superconducting quantum circuits is a pioneering field of research to develop cutting-edge quantum technology, especially quantum
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application! Work assignments This position focuses on the development of theoretically grounded and practically scalable decentralized learning algorithms under realistic system constraints, including
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. Doctoral studies end with a thesis and a doctoral degree. More about being a doctoral student at LTH on lth.se. Subject description This project aims to develop novel algorithms for Neural Rendering
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details and cross-layer interactions with communication and hardware can further affect the actions available to the adversary. We seek to develop analysis and design algorithms that incorporate cross-layer
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. Activities include ultrafast quantum physics, quantum technology with rare earth atoms, quantum states in nanosystems, quantum information theory, quantum spectroscopy, quantum algorithms for optimization
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Are you excited about pioneering experimental quantum computing? Do you want to be part of a world-class research environment developing the next generation of superconducting quantum processors? We
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to the fundamentals and algorithms of spatially and time-multiplexed oscillator-network computing. Duties The PhD student will focus on the fundamentals and algorithms for spatially and time-multiplexed oscillator
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, experience working with the PyTorch framework, documented ability to develop algorithms and implement them in efficient code, and experience in statistical modeling, optimization or numerical methods, as