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PhD Position in Theoretical Machine Learning – Understanding Transformers through Information Theory
Join us for a fully funded PhD position in theoretical machine learning to uncover how and why transformers work. Explore their inner mechanisms using information theory. As part of this project
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of this WASP-financed project is machine learning, in particular dealing with generative models and instabilities associated with cycles of retraining on mixtures of human and machine-generated data
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applications. Project description This PhD project focuses on advancing the field of multi-modal data analysis and generation, integrating computer vision, natural language processing (NLP), and machine learning
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experts in the field of protein engineering, protein production, affinity ligand design and characterization, and machine learning for protein design. This unique PhD position is a 4-year collaborative
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description The postdoctoral project is focused on development and the exploitation of machine learning tools to accelerate the analysis of microtomography data at the MAXIV synchrotron facility. MAXIV
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Engineering and Autonomous Systems division . We offer advanced PhD courses where we extend the fundamentals in optimal control, machine learning, probability theory and similar. The research and learning
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cybersecurity team at Luleå University of Technology and also our partner within Cybercampus Sweden, RISE. We will use methods and technologies including expert systems, evolutionary algorithms, machine learning
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at Stockholm University. We have a strong tradition in sampling but areas that we are growing in include, but are not limited to, Bayesian inference, the intersection of statistics and machine learning
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application! We are now looking for 1-2 PhD students in Automatic Control, at the Department of Electrical Engineering (ISY). Your work assignments The announced positions are within our new competence center
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We are looking for a highly motivated, skilled, and persistent PhD student with experience in computational fluid dynamics (CFD) and some knowledge in structural analysis. The research aims