79 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "Imperial College London" positions at University of Lund in Sweden
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using EEG and advanced machine-learning approaches. The project focuses on identifying neural signatures of recognition and memory retrieval at the single-trial level, with particular emphasis on time
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at the intersection of numerical analysis, uncertainty quantification, and scientific machine learning. The research will primarily focus on probabilistic methods for data-driven model reduction, with
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that are commonly used today. Using the improved noise models, machine learning methods will be used to enhance the segmentation of EEG data into auditory signal and background activity allowing for refined control
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will receive five weeks of training in teaching and learning in higher education and get the opportunity to learn Swedish through the University’s Swedish language courses for new international staff
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to professor. You will receive five weeks of training in teaching and learning in higher education and get the opportunity to learn Swedish through the University’s Swedish language courses for new international
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and validation of machine-learning and statistical models for disease prediction, prognosis, and therapeutic response. Proficient in R, SAS, and other bioinformatic tools for data integration and
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about working with us Work at Lund University | Lund University Ready to shape the future of research? Find more reasons why Lund University and the HT Faculties is right for you here , and learn more
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Work at Lund University | Lund University Ready to shape the future of research? Find more reasons why Lund University and the HT Faculties is right for you here, and learn more about Working in Lund
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Information Technology conducts broad research in cryptography, computer security, wireless and wired networks. The Security Group has around 20 members. The main research areas are cryptography, privacy, and
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mathematics, applied mathematics, mathematical statistics, as well as computer vision and machine learning. The department has approximately 150 employees, including 21 full professors and almost 50 senior