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Join us in designing stable materials for sustainable energy devices with machine-learning-accelerated simulation and modeling. Work assignments The postdoctoral researcher will develop machine
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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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and apply AI and machine-learning methods to infer interaction networks from acoustic co-occurrence and activity patterns, and analyse their structural properties to link topology to response diversity
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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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about research and eduction in cybersecurity at Linköping University is found here: https://liu.se/en/research/cybersecurity As Assistant professor in Computer Science with a specialisation in
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include using large language models to remove treatment-predictive information from text, benchmarking debiasing estimators such as Design-based Supervised Learning and Prediction-Powered Inference
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involve writing and running code to process sequencing data on a computer server, applying statistical models and machine learning algorithms, and performing downstream data analysis, including
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mathematics, or a related field Practical experience with AI, machine learning, data analytics, or related computational methods Ability to apply technical knowledge to real-world problems Experience