20 machine-learning "https:" "https:" "https:" "https:" "https:" "University of St" Postdoctoral positions at University of Lund in Sweden
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Description of the workplace The position will be placed at the division of Computer Vision and Machine Learning at the Centre for Mathematical Sciences. The Centre for Mathematical Sciences is an
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difference! For further information, please visit: https://www.lunduniversity.lu.se/about-lund-university/work-lund-university www.sweden.se https://www.maxiv.lu.se/about-us/careers/compensation-benefits/
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independently Excellent command of the English language, good communication, and team working skills If not already proficient, be willing and able to learn X-ray spectroscopy to a high level. The following
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. Demonstrated experience in computational methods, particularly in deep learning and computer vision. Understanding or willingness to learn advanced statistical modeling is a plus Assessment criteria and other
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University and the HT Faculties is right for you here, and learn more about Working in Lund , Moving to Lund and Living in Lund . Qualifications The assessment will primarily be based on your research merits
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Description of the workplace The Division of Secure and Networked Systems at the Department of Electrical and Information Technology conducts broad research in cryptography, computer security
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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 , Moving to Lund and Living in Lund . Qualifications
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for machine learning, e.g. PyTorch or TensorFlow. Strong ability in spoken and written Swedish. Assessment of the applicants will primarily be based on scientific merits and potential as researchers. Special
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factor that strongly modifies turbulence, pressure drop, and heat transfer. Unlike conventional machined roughness, AM roughness is characterized by randomness, porosity, and powder adhesion, producing
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of the following areas: state models, time series analysis, computational statistics, unsupervised machine learning, optimisation, model predictive control. Experience in financial mathematics. Having high integrity