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propagation problems, stochastic partial differential equations, geometric numerical integration, optimization, biomathematics, biostatistics, spatial modeling, Bayesian inference, high-dimensional data, large
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and calibration of reports from various sources. Collect and analyse large-scale cross-industry accident data using FRAM (Functional Resonance Analysis Method) within LLMs to identify human-, technical
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track record of industrial and academic collaboration globally and has published a large number of papers on 2D materials in Nature Communications, Advanced Materials, Advanced Functional Materials
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Keen on exploring the force of light and develop tomorrows technologiges for contact-free particle manipulation for biotechnology and beyond? Information about the project This postdoc position
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the polymer matrix while preserving the quality of the fibres. Information about the division and the department The position is based in the Division of Materials and Manufacture at the Department
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The position's field of research focuses on developing and implementing safe, transparent, and explainable AI systems using multimodal deep learning and Large Language Models (LLMs) for healthcare
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chemistry and technology to molecular- and data- driven nutrition. In food science, we focus primarily on marine and plant-based food systems with the goal to promote high food quality, minimize losses
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. evaluate and summarize your large amount of complex data, possibily involving state-of-the-art machine learning methods developed in the group by other team members, and share them with our cross-diciplinary
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of the Wallenberg Centre for Quantum Technology (WACQT, http://wacqt.se ). The core project of the centre is to build a quantum computer based on superconducting circuits. You will be part of the Quantum Computing
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collaborative manner. Conducting interviews, workshops, and collecting case study data, translating the case observations into analytical representations, writing and presenting high quality papers, and being