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. [Month 6 – 12] 3. Develop a machine learning model and train it on the existing datasets, [Month 12 – 18]. 4. Collect more data, during the project from one or two grazing experiments to complement
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environmental factors such as fluctuating wind speeds and saltwater exposure. Using advanced statistical and machine learning techniques, including Bayesian inference and stochastic modelling, the project will
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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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acceleration of large-scale machine learning workloads Perform characterization and modeling of electronic and optical devices Develop hardware-aware machine learning models incorporating electronic and optical
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learning video-AI models; b) assess representational alignment of bio-inspired deep learning models to the human brain. The bio-inspired models will be enriched with different temporal integration mechanisms
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, please visit: https://qbm.genzentrum.lmu.de/application/ Tuition fees per semester in EUR None Combined Master's degree / PhD programme No Joint degree / double degree programme No Description/content
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, and advanced machine learning in the engineering domain. Generative AI substantially changes the way engineers interact with and benefit from AI and access domain-specific knowledge, marking a phase
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solutions across the natural sciences. Your workplace You will be employed at the Department of Mathematics in the Division of Applied Mathematics, https://liu.se/en/organisation/liu/mai/tima . The research
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of cardiovascular anatomy and hemodynamics. The research will integrate modern machine learning with MR signal modeling, computational imaging, and fluidmechanis, with the ultimate goal of enabling faster, more
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, water quality and meteorological datasets routinely collected by water utilities. The student will have the opportunity of using state-of-the-art machine learning methods (predictive analytics) to analyse