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chain, ranging from synthesis, cell assembly, characterization, modeling to scaled-up manufacturing. The 2-year postdoctoral project Machine Learning-based Electro-Chemo-Mechanical Estimation and Control
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We are looking for a postdoc to join our team at the Division of Computer and Network Systems. Become part of our innovative group and contribute to exciting research in Computer Architecture within
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simulations, density functional theory (DFT), molecular simulations, or machine-learning potentials. Experience with generative AI, active learning, uncertainty quantification, Bayesian optimization
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also carries information about the treatment assignment, conditioning on it can bias the causal estimate. Your task is to collaborate with our team at CSE that is leading the methods development and then
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, Bayesian optimization, or reinforcement learning. Experience with high-performance computing (HPC). Experience supervising students or junior researchers. What you will do As a postdoctoral researcher, you
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. Subject description Automatic Control comprises the analysis and synthesis of models and model-based algorithms for control, estimation, and monitoring of complex dynamic systems. Project description
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of Technology’s campus in Luleå. Subject description Automatic Control comprises the analysis and synthesis of models and model-based algorithms for control, estimation, and monitoring of complex dynamic systems
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format. The application should be registered via Umeå University’s e-recruitment system Varbi (https://umustipendie.varbi.com/en/what:job/jobID:950146/ ) and submitted by the deadline 17th of September
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and impactful sensing problem: developing machine learning approaches for turning the vibration signals of mining machines into precise, bucket-by-bucket estimates of how finely rock has been fragmented
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. Plant science/ecology, especially related to forest ecosystems. Computer programming. Data analysis (machine learning, statistics, numerical analysis, time-series analysis, etc.). Quantitative methods in