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application! How does AI transform how firms create value and compete? We are launching a new research project to explore how specialised AI models are reshaping the conditions for value creation and innovation
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methods that can accurately model such processes remains an open and active research frontier. This PhD project is fundamentally about advancing that frontier, contributing new methods for generative
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, and modeling of structural heterogeneity in biological macromolecules. Rather than only applying established workflows, you will explore new computational formulations and alternative ways
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emissions and biodiversity impacts related to bank lending, particularly in agriculture. Therefore, banks therefore often must rely on coarse standard values or low‑precision models, making it difficult
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will build an experimental and computational platform based on 3D-printed, brain-mimetic tissue models with tunable transport properties, where interface transport can be measured and predicted
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distributed wireless systems" which is conducted in collaboration between Linköping University (LiU) and Lund University (LU). Read more here: https://elliit.se/project/machine-learning-for-sensing-in
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equations. Your main research assignments will be to develop new models and methods for generative sampling and Bayesian inference. You will be jointly supervised by Assistant Prof. Zheng Zhao (https
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conducted in collaboration between Linköping University (LiU) and Lund University (LU). Read more here: https://elliit.se/project/machine-learning-for-sensing-in-distributed-wireless-systems/ Distributed MIMO
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application! We are looking for a PhD student for sustainable and resource-efficient machine learning. Your work assignments Machine learning has recently advanced through scaling model sizes, training budgets
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teaching in key and rapidly evolving areas such as autonomous systems, data-driven modeling, learning-based control, optimization, complex networks, and sensor fusion. Research at the division is