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. This project will develop responsive manufacturing technology that will have sufficient flexibility to overcome such problems by utilizing intelligent machine learning to control the printing process in real
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the complex multiscale nonlinear interactions at the origin of such extreme events. In this project, you will develop machine learning-based reduced-order models which can accurately forecast
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the development and application of probabilistic inference methods and machine learning techniques for quantitative uncertainty modeling and for the integration of heterogeneous climate data
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The Faculty of Engineering, Department Electronics and Informatics, Research Group Electronics and Informatics: Research – Development - Innovation is looking for a PhD-student with a doctoral grant
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ecosystem applications within AgTech (https://agtechsweden.com/ ), search-and-rescue operations in challenging terrain, and intelligent surveillance for societal security. By combining machine learning with
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materials systems at the molecular level with machine learning. The PhD Student will undertake a study analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for
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other researchers, industry and end-users. • Aptitude in a relevant area (e.g. data analysis, machine learning, rail engineering, asset management, hydrology, hydraulics) as evidenced by previous
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25th February 2026 Languages English English English The Department of Materials Science and Engineering has a vacancy for a PhD Candidate in machine learning and large language models (LLMs
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postdocs, tenure-track positions, tenured positions, and positions for distinguished professorship. Candidates in areas including, but not limited to, Quantum Algorithms, Quantum Machine Learning, Quantum
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cutting-edge research in areas such as pattern recognition, automation science, complex systems, AI for Science, robotics, machine learning, computer vision, natural language processing, biometrics, medical