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PhD in Materials Science Norrkoping Reference number LiU-2026-03852 Join us in developing machine-learning accelerated simulation methods to understand and optimize interfaces in hybrid organic
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PhD student focusing on Machine Learning of Geometric Representations at ISY Linkoping Reference number LiU-2026-03853 We have the power of over 50,000 students and co-workers. Students who provide
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professional network between PhD-students, researchers and industry. Read more: https://wasp-sweden.org/graduate-school/ Your work assignments Machine learning, and in particular deep learning, requires
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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. https://www.lth.se/english/study-at-lth/phd-studies/ AEGIS — Adaptive Grid-Interactive
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Computational Fluid Dynamics (CFD), fluid mechanics, and Artificial Intelligence (AI), with a particular focus on developing deep reinforcement learning methods for active flow control of hydraulic
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impact on sustainability and future technologies. For more information: https://saragovi.science/ Being a doctoral student As a doctoral student, you are both admitted as a student and employed at Lund
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participating in the DARPA SUB-T challenge with the CoSTAR Team lead by NASA/JPL ( https://costar.jpl.nasa.gov/ ). Subject description Robotics and artificial intelligence aim to develop novel robotic
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Intelligence and Machine Learning development, Proficiency in written and oral communication in English. Place of employment: Karlskrona. Employment level: 100%. Commencement: Early Fall 2026, exact
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features. No cookies to display. Reject Save My Preferences Accept Skip to content PhD student in Machine Learning with a focus on mathematical and statistical methods for uncertainty quantification
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engineering systems through a model-driven approach, i.e. a combination of simulation- and data-driven methods and tools with data analysis and machine learning as an important part. The work builds on